Data Scientist Jobs in California

STAND 8 provides end to end IT solutions to enterprise partners across the United States and with offices in Los Angeles, New York, New Jersey, Atlanta, and more including internationally in Mexico and India. We are seeking an experienced and highly skilled Senior Data Scientist to lead the development and deployment of innovative data science solutions. The ideal candidate has deep expertise in statistical modeling, programming in R and/or Python, and a proven ability to communicate complex concepts in a clear and accessible way. This role will involve working closely with both technical and non-technical stakeholders, mentoring team members, and ensuring that models are built with accuracy, fairness, and sustainability in mind. If you're driven by solving meaningful problems with data and enjoy mentoring teams and building scalable systems, we'd love to hear from you. Responsibilities Develop and maintain data science models using R and/or Python Build statistical, predictive, and forecasting models, considering algorithmic bias and ethical implications Lead end-to-end development of data science solutions, including requirements gathering, coding, deployment, performance evaluation, and optimization Translate model logic and outcomes into simulations and actionable insights for both technical teams and business users Collaborate using tools such as Posit Workbench, Databricks, Hex, or similar platforms Provide hands-on training to the Data Science team in version control using GIT, and transfer knowledge on modeling techniques and statistical methods Explain complex statistical concepts in simple, understandable language to non-technical stakeholders Configure, maintain, and troubleshoot Linux servers hosting data science tools Create thorough documentation of code, software environments, server settings, and workflow processes to ensure long-term maintainability Work within or support organizations in government, school districts, or related public sector settings (preferred) Qualifications Master's or Ph.D. in Computer Science, Applied Mathematics, Statistics, Data Science, or a related field from an accredited university in the United States A minimum of eight (8) years of experience in delivering services related to data science as described in the Statement of Work (SOW) Demonstrated proficiency in R and/or Python for data science applications Proven track record of building and deploying statistical and forecasting models Deep understanding of algorithmic bias and its implications in real-world systems Strong communication skills with the ability to present technical concepts to both technical and non-technical audiences Experience using GIT for version control in collaborative environments Familiarity with Linux systems and the ability to configure and manage data science tools in that environment Commitment to writing clean, maintainable code and thorough documentation Experience in government or educational institutions is highly desirable Additional Details The base range for this contract position is $90-100/per hour, depending on experience. Our pay ranges are determined by role, level, and location. The range displayed on each job posting reflects the minimum and maximum target for new hires of this position across all US locations. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Qualified applicants with arrest or conviction records will be considered. Benefits Medical coverage and Health Savings Account (HSA) through Anthem Dental/Vision/Various Ancillary coverages through Unum 401(k) retirement savings plan Company-paid Employee Assistance Program (EAP) Discount programs through ADP WorkforceNow About Us STAND 8 provides end-to-end IT solutions to enterprise partners across the United States and globally with offices in Los Angeles, Atlanta, New York, Mexico, Japan, India, and more. STAND 8 focuses on the "bleeding edge" of technology and leverages automation, process, marketing, and over fifteen years of success and growth to provide a world-class experience for our customers, partners, and employees. Our mission is to impact the world positively by creating success through PEOPLE, PROCESS, and TECHNOLOGY. Check out more at ************** and reach out today to explore opportunities to grow together! By applying to this position, your data will be processed in accordance with the STAND 8 Privacy Policy.

Data Scientist/Growth Engineer - Growth-Focused Role at a Fast-Moving AI Startup San Francisco (Onsite) | Early-stage | High ownership Our client is a fast-scaling, founder-led AI startup backed by top-tier investors. They're building a high-output engineering team and looking for a Data Scientist to help drive growth through first-principles thinking and data-led strategy. This isn't a back-office analytics role - this is about being in the room where bets are made. You'll work directly with founders to shape GTM strategy, analyze user behavior, and help define the playbook for scale. What you'll do: Analyze customer and usage data to find patterns that guide outbound, marketing, and product focus. Work hand-in-hand with the GTM team to identify high-conviction opportunities and eliminate wasted motion. Build the dashboards and reporting infra that inform the leadership team's most critical decisions. Surface actionable insights fast - even when the data is messy, incomplete, or ambiguous. Help build a data-first culture across product, growth, and execs. You might be a fit if: You've done data science or analytics in a high-growth environment (ideally early-stage or startup). You're energized by helping a company find product-market fit and scale it. You've worked closely with sales, growth, or marketing teams before - and know how to translate insight into revenue. You're sharp with SQL, Python, and modern BI tools - but more importantly, you know how to ask the right questions. Bonus: you've seen zero-to-one growth before, and you're ready to do it again - faster. Why this role? You'll be one of the first data hires at a rocketship startup, with a direct line to the CEO and leadership team. Every insight you generate will inform how the company grows. You'll work in a sharp, in-person team where output matters more than credentials. Real equity. Real ownership. Real impact. We're moving fast on this one - reach out if you want to be considered.

👩 💻 Senior Data Scientist / Researcher 💊 Seed Biotech going through it's growth faze 📍 Los Angeles (can be remote within US with monthly travel) 💸 Competitive base + hefty equity About We are working with a team that is building the next generation of intelligent discovery tools for biology. They're reimagining how scientists interact with knowledge, data, and AI to accelerate insights across genomics, disease mechanisms, therapeutics, and beyond. Join them in shaping how foundational models are applied to real-world biomedical questions. Responsibilities Collaborate closely with ML engineers, domain scientists, and product teams to build and validate AI models that unlock insights from multi-omics, biomedical literature, and experimental datasets. Develop and evaluate embeddings, retrieval systems, and generative models for use in scientific knowledge extraction. Translate complex biomedical questions into tractable data problems. Prototype novel methods and contribute to internal research efforts on foundation models in biology. Qualifications A PhD or MS in Computational Biology, Bioinformatics, Biostatistics, or related field - or equivalent experience in applied biomedical research. Strong Python and data science skills (e.g., NumPy, pandas, scikit-learn, PyTorch). Familiarity with scientific datasets (e.g., GEO, UniProt, PubMed, TCGA, PDB) and domain-specific ontologies (e.g., GO, UMLS, MeSH). Experience working with large-scale biomedical data: transcriptomics, genomics, proteomics, or clinical. Bonus: Experience with LLMs, embeddings, or biomedical NLP (e.g., BioBERT, SciSpacy). 📧 Interested in applying? Please click on the ‘Easy Apply' button or alternatively email me your resume at ************************ ⚡ Storm3 is a HealthTech & Biotech recruitment firm with clients across major Tech hubs in Europe, APAC and North America. To discuss open opportunities or career options, please visit our website at storm3.com and follow the Storm3 LinkedIn page for the latest jobs and int el

Job Title: Data Science - Fraud Analytics Employment: FTE Salary : $100,000 - $165,000 p.a. plus upto 10% Variable pay plus benefits (Based on Exp) Years of experience: 3-8 Straive is a global leader in enterprise-grade data analytics and AI solutions, committed to empowering businesses across various industries with cutting-edge technology and expert insights. Backed by EQT, a top private equity firm, we are uniquely positioned to drive innovation through significant investments and an entrepreneurial spirit. Our core focus is on delivering advanced Data Analytics & AI Solutions. By combining sophisticated technology with subject matter expertise, we deliver material impact on our clients' topline and streamline their operations. We specialize in providing tailored solutions across financial services, CPG, legal, pharma, life sciences, retail, sports, entertainment and logistics, helping them build robust data analytics and AI capabilities. With a client base spanning 30 countries, Straive's strategically located teams operate from eight countries and is headquartered in Singapore. This global presence enables us to offer localized expertise with a worldwide perspective. Join Straive to be part of a dynamic team at the forefront of data analytics and AI innovation. Here, you'll have the opportunity to contribute to transformative projects, supported by significant investments and an entrepreneurial drive fueled by our partnership with EQT. Website: ************************ Linkedin Job Role: Data Science - Fraud Analytics Type: FTE Location: New York, NY/San Jose, CA Roles and Responsibilities: · Utilize data analytics tools and methodologies to conduct in-depth assessments and generate Fraud rules and reports on fraud trends (including Merchant Fraud, first-party and third-party fraud). · Investigate suspicious activities and transactions, determine root causes and develop strategies and statistical models to prevent future occurrences. · Develop Fraud rules on workflow systems ·Develop fraud reports for ongoing monitoring of fraud events. ·Generate reports and presentations outlining fraud risks, incidents, and mitigation strategies for management review. ·Collaborate with cross-functional teams, including risk management, operations, and compliance, to enhance fraud prevention measures. ·Monitor industry trends, regulatory changes, and best practices to continually enhance fraud prevention strategies. Skills Required: ·Bachelor's degree in engineering, technology, computer science or related field. ·3+ years of proven data analytics experience in fraud prevention, risk management, or a related field ·Familiarity with fraud detection software, risk assessment methodologies, and regulatory compliance. ·Excellent communication and presentation skills with the ability to convey complex information clearly and concisely. · Detail-oriented with a proactive mindset toward problem-solving and risk mitigation. · Ability to work collaboratively in a cross-functional team environment. Straive Package Benefits Medical, Dental, and Vision Insurance Group Life Insurance and Accident and Death Coverage for Employee Business Travel Accident Insurance 401(k) Employee Retirement Plan Personal Time Off (PTO) Annual Merit Increase (AMI)

At HAYA Therapeutics, we are revolutionizing RNA-guided genome-targeting therapies to treat fibrosis, heart failure, and other serious diseases associated with aging. Our innovative platform leverages long non-coding RNAs (lnc RNAs)-key regulators within the “dark matter” of the genome-to develop first-in-class, highly specific therapies that modulate gene expression and restore cellular function. Recognized for our innovation, HAYA received the prestigious Innosuisse Certificate for Sustainable Growth and has been nominated as TOP Innovative Companies in Switzerland 2025. HAYA's vision is to pioneer the development of next-generation biopharma, leveraging causal disease biology and AI-enabled functional genomics and systems biology to develop precision disease-modifying therapies for common and chronic diseases. By unlocking the full potential of the regulatory genome, our platform enables rapid de-risked target discovery and scalable drug development across multiple therapeutic areas. As a fast-growing biotech, we offer an entrepreneurial, science-driven environment where you'll have a direct impact on shaping our pipeline and advancing RNA medicine. Position Summary: HAYA Therapeutics is seeking a talented and experienced Computational Biologist with deep knowledge of cardiac biology and transcriptomics to join our data science team. In this highly collaborative and impactful role, you will leverage bulk, single-cell and single-nuclei transcriptomic and epigenomic omics data to drive translational research and biomarker discovery in cardiac settings. You will apply innovative computational approaches to uncover novel biology and therapeutic opportunities relevant to cardiac diseases. HAYA deploys a combination of experimental and computational solutions for target and drug discovery in the non-coding regulatory genome space. To this end, we leverage multiple omics modalities, including transcriptomic profiling (e.g., single-cell and single-nuclei RNA-Seq, bulk RNA-Seq). You will apply your end-to-end expertise in transcriptomics data preprocessing and downstream analysis to contribute to scientific discoveries and the advancement of our precision RNA-based therapeutics for cardiovascular diseases. The entire Data Science team across Haya programs will use the analysis templates and approaches you establish to handle complex datasets. The Data Science team is central to HAYA's vision by pioneering innovative AI and advanced computational biology solutions to overcome current scientific, methodological, and operational bottlenecks. We leverage complex biological datasets to remove operator biases, enabling the rapid end-to-end execution of HAYA's pipeline. Our approach ensures precision-driven decision-making, which enables target drug discovery, biomarkers, translational, clinical, and business strategies, reinforcing HAYA as a leader of next-generation biopharma. What's in it for me? At HAYA, you won't just analyze data - you'll help shape the future of RNA-based therapeutics. This is a unique opportunity to apply your scientific expertise to uncover novel biology in the non-coding regulatory genome and translate those discoveries into real therapeutic potential. You'll be part of a deeply collaborative and forward-thinking team, working at the intersection of data science, functional genomics, and drug discovery. Here, your insights won't sit on a shelf - they'll directly influence the development of treatments for patients with serious cardiovascular and fibrotic diseases. We offer a dynamic, innovative culture where scientific curiosity is celebrated, your voice is heard, and your growth is supported. Whether you're leading high-impact projects, engaging with cross-functional teams, or learning something new every day, you'll find a meaningful and rewarding career path at HAYA. Key Responsibilities: Perform bulk, single-cell, and single-nuclei transcriptomics computational analysis, mainly on (but not limited to) cardiac tissue and disease-related data. Be an internal expert on cardiac transcriptomics, consulted across multiple settings including target MoA and validation, biomarkers, translation, and pre-clinical and clinical settings. Conduct in-depth investigations using both in-house and publicly available datasets to uncover cardiac disease- and perturbation-specific cell states and transcriptional programs. Integrate transcriptomic data (including single-cell data and bulk RNA-Seq) from multiple independent datasets to inform biomarker discovery and validation strategies. Prepare and communicate high-quality scientific reports, visualizations, and presentations for both technical and cross-functional stakeholders. Education & Experience: PhD in computational sciences (e.g., bioinformatics, computer science) or life sciences with a strong computational focus, or equivalent industry experience (6+ years). Deep expertise in transcriptomic data analysis, including single-cell and single-nuclei RNA-Seq and bulk RNA-Seq data analysis, covering preprocessing, integration, and biological interpretation. Deep knowledge on cardiac biology and cardiac diseases, including HCM and HF, and ability to relate it to transcriptional dynamics across different cell types and states. Proven ability to integrate data from multiple sources to construct clear, biologically meaningful narratives, with a demonstrated track record of delivering high-quality single-cell/nuclei RNA-Seq and bulk RNA-Seq data packages. Proficient in R or Python, with experience working in Linux-based computing environments, including remote server access and basic Bash scripting. Experience with primary epigenomic data analysis (e.g., ATAC-Seq, PRO-Seq, GRO-Seq, CUT&RUN, chromatin conformation capture) to identify functional regions in the regulatory genome is a plus. Excellent written and verbal communication skills in English, with the ability to clearly present complex data to diverse audiences. HAYA Therapeutics is an Equal Opportunity Employer committed to fostering a diverse, inclusive, and equitable workplace where all individuals feel valued and empowered. We provide equal employment opportunities to all qualified applicants and employees without regard to race, color, religion, sex (including pregnancy, sexual orientation, gender identity, or gender expression), national origin, ancestry, age, marital or familial status, veteran status, disability, genetic information, or any other characteristic protected by applicable federal, state, or local laws. We prohibit discrimination and harassment of any kind and are committed to ensuring fair and equitable treatment in all aspects of recruitment, hiring, promotion, compensation, benefits, training, and career development. At HAYA, we believe that diversity of thought, experience, and background drives innovation and strengthens our mission to transform patient care through cutting-edge RNA-based therapeutics.

Seeking Founding Data Scientists and Machine Learning Engineers Palladio AI | San Francisco Bay Area (Hybrid) Imagine Multiplying Your Impact You've unlocked major wins in your career - you've shipped models, moved key metrics, and proved what great data science and machine learning can do. You've bent the curve for products used by millions of people. Now, picture the idea of leveling up the entire app ecosystem by scaling your impact across many products and companies so every app in your pocket becomes smarter, more engaging, and more essential to the people who rely on it. You can help product teams iterate faster, delight users, and grow revenue, all because of the intelligence you build once and deploy everywhere. We know this ambition: we've done this again and again at places like Uber, Apple, Meta, Google, and Chime. We've had tens of billions of dollars of impact for products essential to billions of people, and we're ready to scale our impact to the next level. If this sounds like the next chapter you're looking for, read on. Why Palladio Exists Dashboards describe the past; teams need their next move . Palladio AI is the intelligence layer between raw data and decisive action, surfacing product opportunities that turn into real growth levers and guiding action so product teams iterate with confidence and velocity instead of sifting through noise. What You'll Shape Our team is building core systems in behavioral modeling, causal inference, forecasting, agentic platforms, and more. You'll help extend those domains: building ML and AI models to detect and surface product opportunities, shipping learning loops that improve themselves with every release. In short, you'll turn first-principles data science into a product that scales across industries. More than any technical challenge, you'll build a platform that helps real people make better decisions, turning data into clarity and clarity into progress. About You Craft and excellence. You dive into messy data, prototype quickly, and iterate until the insight sings. Impact mindset. 6+ years in production ML/DS; you balance scientific rigor with “it ships today, iteration on the way” pragmatism. Owner at heart. Zero-to-one energizes you; you'd rather set the standard than inherit one. Product voice. You can walk a PM through trade-offs as confidently as you tune a model. Customer-obsessed. You connect with the user's pain, measure success in user outcomes, and translate findings into product wins. Beginner's Mind. You stay hungry to learn, because better ideas are always out there. Our Team Our team has shaped the design, data, and systems behind some of the world's most iconic products. We're builders who founded Uber's Michelangelo, led data and design teams at Apple, Meta, Google, and Chime, and shipped products used by billions. We've had tens of billions of dollars of impact. Backed by top-tier investors, we're now channeling that experience into a focused, user-obsessed startup so every product team can tap the same class of intelligence at scale. Why Join Now This is the moment to have an outsized impact. You'll work directly with founders and early customers to define not just features but also the fundamental approach to how product intelligence should work. You'll see your ideas in production quickly, affecting real decisions for products used by millions. We're building a company that values clarity, craft, and impact. If those values resonate with you, we'd love to connect. Ready for the next level of impact? Reach us at ************************. Let's build breakthroughs together!

As a Senior Data Scientist, you will play a key role in empowering consumers and creating business value by designing, developing, and deploying intelligent solutions across a diverse range of clients including Financial Institutions, FinTechs, SMEs, Large Enterprises, and Government Agencies. You will focus on delivering "Certainty as a Service" through explainable and trustworthy models in domains such as lending, financial decisioning, management, and payments. Key Responsibilities: Design, develop, and deploy advanced machine learning and deep learning models for production use. Create consumable metrics, explainability frameworks, and confidence measures for decision-making solutions. Drive insights from complex and diverse datasets, including structured, unstructured, and time-series data. Work across Verification Services, Entity Resolution, Attribute & Temporal Analysis, and related platforms. Perform advanced error analysis, dimensionality reduction, and model interpretability assessments. Translate business problems into data science solutions in lending, credit scoring, and financial management. Collaborate with cross-functional teams to ensure successful deployment via Kubernetes, Docker, APIs, and event-driven architecture. Communicate findings clearly with both technical and non-technical stakeholders. Required Qualifications: Master's Degree or higher in Data Science, Computer Science, Information Systems, or a closely related field. A Ph.D. is preferred. 10+ years of commercial experience in Machine Learning / Deep Learning, including model development and deployment. Strong experience in Python for data science and software development. Solid foundation in: Natural Language Understanding (NLU). Computer Vision. Statistical Modeling Data Visualization. Classical and Advanced ML methods. Experience in model interpretability and explainability. Demonstrated ability to solve novel problems in the financial domain. Strong experience with Kubernetes, Docker, REST APIs, GraphQL, and event streaming. Excellent written and verbal communication skills. Preferred Qualifications: Exposure to credit risk modeling, risk evaluation, and financial decision systems. Experience in Finance or FinTech domains. Expertise in discrete, differential, deterministic, and probabilistic mathematical modeling. Advanced skills in Transformer models, Attention Mechanisms, PCA or other dimensionality reduction techniques. Strong background in Data Architecture, Query Optimization, and ML Ops. Familiarity with positive attribution techniques, decision science in lending, and attribute analysis.

LinkedIn is the world's largest professional network, built to help members of all backgrounds and experiences achieve more in their careers. Our vision is to create economic opportunity for every member of the global workforce. Every day our members use our products to make connections, discover opportunities, build skills and gain insights. We believe amazing things happen when we work together in an environment where everyone feels a true sense of belonging, and that what matters most in a candidate is having the skills needed to succeed. It inspires us to invest in our talent and support career growth. Join us to challenge yourself with work that matters. At LinkedIn, our approach to flexible work is centered on trust and optimized for culture, connection, clarity, and the evolving needs of our business. The work location of this role is hybrid, meaning it will be performed both from home and from a LinkedIn office on select days, as determined by the business needs of the team. LinkedIn's Data Science team leverages big data to empower business decisions and deliver data-driven insights, metrics, and tools in order to drive member engagement, business growth, and monetization efforts. With over 1 billion members around the world, a focus on great user experience, and a mix of B2B and B2C programs, a career at LinkedIn offers countless ways for an ambitious data scientist to have an impact. We are seeking a talented and driven individual to accelerate our efforts and contribute to LinkedIn's data-centric culture. In this role, you will tackle a wide range of technical challenges spanning products, engineering, research, data engineering, finance, and infrastructure. Leveraging data and analysis, you will address critical challenges within our infrastructure organization, shaping product strategy and guiding investment decisions with data-driven insights. LinkedIn's infrastructure is the backbone of our operations, encompassing datacenters, servers, network infrastructure, power systems, and foundational software platforms that power our products and services. Responsibilities • Work with a team of high-performing analytics, data science professionals, and cross-functional teams to identify business opportunities and develop algorithms and methodologies to address them. • Analyze large-scale structured and unstructured data. • Develop methodologies to enhance LinkedIn's operations and platform capabilities. • Apply technical expertise to our forecasting and capacity planning process to seek opportunities of improvement • Engage with technology partners to build, prototype and validate scalable tools/applications end to end (backend, frontend, data) for converting data to insights. • Promote and enable adoption of technical advances in Data Science; elevate the art of Data Science practice at LinkedIn. • Improve LinkedIn's ability to measure and credibly speak to labor market trends and other economic phenomena. • Initiate and drive projects to completion independently. • Act as a thought partner to senior leaders to prioritize/scope projects, provide recommendations and evangelize data-driven business decisions in support of strategic goals. • Partner with cross-functional teams to initiate, lead or contribute to large-scale/complex strategic projects for team, department, and company. • Provide technical guidance and mentorship to junior team members on solution design as well as lead code/design reviews. Basic Qualifications: • Bachelor's Degree in a quantitative discipline: Statistics, Operations Research, Computer Science, Informatics, Engineering, Applied Mathematics, Economics, etc. • 5+ years of industry or relevant academia experience • Background in at least one programming language (eg. R, Python, Java, Ruby, Scala/Spark or Perl) • Experience in applied statistics and statistical modeling in at least one statistical software package, (eg. R, Python) Preferred Qualifications: • 7+ years of industry or relevant academia experience • MS or PhD in a quantitative discipline: Statistics, Operations Research, Computer Science, Informatics, Engineering, Applied Mathematics, Economics, etc. or other quantitative field. • Experience in infrastructure planning, operations research, or a related field • Familiarity with cloud computing platforms and infrastructure management systems. Suggested Skills • Statistical Modeling • Forecasting • Programming • Data Analysis • Infrastructure Planning You will Benefit from our Culture: We strongly believe in the well-being of our employees and their families. That is why we offer generous health and wellness programs and time away for employees of all levels. LinkedIn is committed to fair and equitable compensation practices. The pay range for this role is $164,000 - $268,000. Actual compensation packages are based on several factors that are unique to each candidate, including but not limited to skill set, depth of experience, certifications, and specific work location. This may be different in other locations due to differences in the cost of labor. The total compensation package for this position may also include annual performance bonus, stock, benefits and/or other applicable incentive compensation plans. For more information, visit ************************************** Equal Opportunity Statement We seek candidates with a wide range of perspectives and backgrounds and we are proud to be an equal opportunity employer. LinkedIn considers qualified applicants without regard to race, color, religion, creed, gender, national origin, age, disability, veteran status, marital status, pregnancy, sex, gender expression or identity, sexual orientation, citizenship, or any other legally protected class. LinkedIn is committed to offering an inclusive and accessible experience for all job seekers, including individuals with disabilities. Our goal is to foster an inclusive and accessible workplace where everyone has the opportunity to be successful. If you need a reasonable accommodation to search for a job opening, apply for a position, or participate in the interview process, connect with us at [email protected] and describe the specific accommodation requested for a disability-related limitation. Reasonable accommodations are modifications or adjustments to the application or hiring process that would enable you to fully participate in that process. Examples of reasonable accommodations include but are not limited to: -Documents in alternate formats or read aloud to you -Having interviews in an accessible location -Being accompanied by a service dog -Having a sign language interpreter present for the interview A request for an accommodation will be responded to within three business days. However, non-disability related requests, such as following up on an application, will not receive a response. LinkedIn will not discharge or in any other manner discriminate against employees or applicants because they have inquired about, discussed, or disclosed their own pay or the pay of another employee or applicant. However, employees who have access to the compensation information of other employees or applicants as a part of their essential job functions cannot disclose the pay of other employees or applicants to individuals who do not otherwise have access to compensation information, unless the disclosure is (a) in response to a formal complaint or charge, (b) in furtherance of an investigation, proceeding, hearing, or action, including an investigation conducted by LinkedIn, or (c) consistent with LinkedIn's legal duty to furnish information. Pay Transparency Policy Statement As a federal contractor, LinkedIn follows the Pay Transparency and non-discrimination provisions described at this link: ******************************** Global Data Privacy Notice for Job Candidates This document provides transparency around the way in which LinkedIn handles personal data of employees and job applicants: ***************************************

W2 only (No C2C or 3rd Parties) Looking for a Data Engineer - Human Behavior and Carbon Neutrality who is interested in the overlap between technology and the behavioral sciences to architect and optimize cloud-based infrastructure to support research objectives in the Carbon Neutrality Department of the Human-Centered AI Division. In this role, you will design, develop, and maintain end-to-end data pipelines in Databricks for processing/analyzing large-scale datasets, as well as build and optimize cloud-based infrastructure to support generative AI methods, ensuring scalability, reliability, and performance. We're looking for someone with a Bachelor's degree or higher in Computer Science, Engineering, or a related field, and 4+ years of experience designing, building, and maintaining data pipelines in a cloud environment, preferably using Databricks. As a Data Engineer - Human Behavior and Carbon Neutrality, you will: Design, develop, and maintain end-to-end data pipelines in Databricks for processing/analyzing large-scale datasets. Build and optimize cloud-based infrastructure to support generative AI methods, ensuring scalability, reliability, and performance. Collaborate closely with research scientists, software developers, machine learning engineers, and domain experts to understand data requirements and design effective solutions. Implement best practices for data quality, data integrity, and data security throughout the pipeline. Incorporate multi-model data (e.g., vision, language, and time series) techniques into data pipelines to enable AI model development. Monitor and troubleshoot data pipelines, identifying/resolving performance bottlenecks, and optimizing resource utilization. Stay up-to-date with the latest advancements in cloud technologies, generative AI frameworks, and data engineering techniques. Requirements Bachelor's or Master's degree in Computer Science, Engineering, or a related field 4+ years of experience designing, building, and maintaining data pipelines in a cloud environment, preferably using Databricks Strong proficiency in cloud technologies, especially AWS A track record of working with human behavior data and the ability to derive actionable insights from such data is a plus Expertise in SQL and Python Experience building and maintaining live dashboards to monitor user behavior, product stability, and model performance Strong problem-solving skills, attention to detail, and the ability to work effectively in a collaborative, cross-functional team environment Excellent communication skills to convey complex technical concepts to both technical and non-technical stakeholders Bonus Qualifications: Expertise in AI/ML frameworks like TensorFlow or PyTorch, with hands-on experience in deploying/optimizing deep learning models Familiarity with AI model training and fine tuning techniques, including an understanding of the challenges associated with multi-modal data Proficiency in additional languages such as R, Scala, or Java Experience with containerization and orchestration tools like Docker and Kubernetes Experience with NoSQL, Change Data Capture Techniques, and BI Tools Benefits: PTO and paid holidays! Pre-tax commuter benefits Employer Subsidized healthcare benefits Flexible Spending Account for healthcare-related costs Employer covers all costs for short- and long-term disability and life insurance 401k package

About us: Intuitive is an innovation-led engineering company delivering business outcomes for 100's of Enterprises globally. With the reputation of being a Tiger Team & a Trusted Partner of enterprise technology leaders, we help solve the most complex Digital Transformation challenges across following Intuitive Superpowers: Modernization & Migration Application & Database Modernization Platform Engineering (IaC/EaC, DevSecOps & SRE) Cloud Native Engineering, Migration to Cloud, VMware Exit FinOps Data & AI/ML Data (Cloud Native / DataBricks / Snowflake) Machine Learning, AI/GenAI Cybersecurity Infrastructure Security Application Security Data Security AI/Model Security SDx & Digital Workspace (M365, G-suite) SDDC, SD-WAN, SDN, NetSec, Wireless/Mobility Email, Collaboration, Directory Services, Shared Files Services Intuitive Services: Professional and Advisory Services Elastic Engineering Services Managed Services Talent Acquisition & Platform Resell Services About the job: Title: Imaging Data Engineer/Architect Start Date: Immediate # of Positions: 1 Position Type: Contract/ Full-Time Location: San Francisco (Onsite/ Hybrid) About the Role We are seeking a highly skilled Imaging Data Engineer/Architect to join our San Francisco team as a Subject Matter Expert (SME) in radiology and digital pathology. This role will design and manage imaging data pipelines, ensuring seamless integration of clinical data and metadata to support advanced diagnostic and research applications. The ideal candidate will have deep expertise in medical imaging standards, cloud-based data architectures, and healthcare interoperability, contributing to innovative solutions that enhance patient outcomes. Responsibilities Design and implement scalable data architectures for radiology and digital pathology imaging data, including DICOM, HL7, and FHIR standards. Develop and optimize data pipelines to process and store large-scale imaging datasets (e.g., MRI, CT, histopathology slides) and associated metadata. Collaborate with clinical teams to understand radiology and pathology workflows, ensuring data solutions align with clinical needs. Ensure data integrity, security, and compliance with healthcare regulations (e.g., HIPAA, GDPR). Integrate imaging data with AI/ML models for diagnostic and predictive analytics, working closely with data scientists. Build and maintain metadata schemas to support data discoverability and interoperability across systems. Provide technical expertise to cross-functional teams, including product managers and software engineers, to drive imaging data strategy. Conduct performance tuning and optimization of imaging data storage and retrieval systems in cloud environments (e.g., AWS, Google Cloud, Azure). Document data architectures and processes, ensuring knowledge transfer to internal teams and external partners. Stay updated on emerging imaging technologies and standards, proposing innovative solutions to enhance data workflows. Qualifications Education: Bachelor's degree in computer science, Biomedical Engineering, or a related field (master's preferred). Experience: 5+ years in data engineering or architecture, with at least 3 years focused on medical imaging (radiology and/or digital pathology). Proven experience with DICOM, HL7, FHIR, and imaging metadata standards (e.g., SNOMED, LOINC). Hands-on experience with cloud platforms (AWS, Google Cloud, or Azure) for imaging data storage and processing. Technical Skills: Proficiency in programming languages (e.g., Python, Java, SQL) for data pipeline development. Expertise in ETL processes, data warehousing, and database management (e.g., Snowflake, BigQuery, PostgreSQL). Familiarity with AI/ML integration for imaging data analytics. Knowledge of containerization (e.g., Docker, Kubernetes) for deploying data solutions. Domain Knowledge: Deep understanding of radiology and digital pathology workflows, including PACS and LIS systems. Familiarity with clinical data integration and healthcare interoperability standards. Soft Skills: Strong analytical and problem-solving skills to address complex data challenges. Excellent communication skills to collaborate with clinical and technical stakeholders. Ability to work independently in a fast-paced environment, with a proactive approach to innovation. Certifications (preferred): AWS Certified Solutions Architect, Google Cloud Professional Data Engineer, or equivalent. Certifications in medical imaging (e.g., CIIP - Certified Imaging Informatics Professional).

We are hiring a Data Engineer with 2-3 years of experience in building and maintaining data pipelines, ETL processes, and data infrastructure. The ideal candidate has hands-on skills in SQL, Python, and working with large datasets in cloud or traditional data environments. As a Data Engineer, you will work closely with analytics teams to ensure high data quality, integrity, and performance. Responsibilities: Design, build, and optimize data pipelines Develop and manage ETL/ELT workflows Support database performance tuning and data modeling Work with cloud-based storage and compute platforms (AWS, GCP, or Azure) Collaborate with data analysts and other engineers Requirements: 2-3 years of experience in data engineering or backend development Strong SQL and Python skills Familiarity with ETL tools and data warehouse architecture Exposure to cloud services (AWS, Azure, or GCP) is a plus Must be a U.S. Citizen or Green Card Holder

A client of Sharp Decisions Inc. is actively seeking to hire an IT Specialist/Data Engineer professional for a position located in Rosemead CA. *W2 and Local only. (C2C candidates are not illegible) US Citizen/Green Card holder Title: IT Specialist/Data Engineer Location: Rosemead CA 91770 Pay: $40.34 Day-to-Day Responsibilities/Workload Mapping identified source data to new cloud structures. Re-engineering 20,000 lines of existing SAS transformation logic into Power Query Online (M language). This is the core effort of the project. Replace related legacy diver and month end processing SAS code. Integrating data from the new Enablon system once available, ensuring a smooth transition. Required Skills/Attributes: The transition requires proficiency in the Microsoft data ecosystem (Power Query/M, Power BI Dataflows, cloud storage concepts). SAS Desired Skills/Attributes: 3 years' experience Python SQL

Data Scientist/Growth Engineer - Growth-Focused Role at a Fast-Moving AI Startup San Francisco (Onsite) | Early-stage | High ownership Our client is a fast-scaling, founder-led AI startup backed by top-tier investors. They're building a high-output engineering team and looking for a Data Scientist to help drive growth through first-principles thinking and data-led strategy. This isn't a back-office analytics role - this is about being in the room where bets are made. You'll work directly with founders to shape GTM strategy, analyze user behavior, and help define the playbook for scale. What you'll do: Analyze customer and usage data to find patterns that guide outbound, marketing, and product focus. Work hand-in-hand with the GTM team to identify high-conviction opportunities and eliminate wasted motion. Build the dashboards and reporting infra that inform the leadership team's most critical decisions. Surface actionable insights fast - even when the data is messy, incomplete, or ambiguous. Help build a data-first culture across product, growth, and execs. You might be a fit if: You've done data science or analytics in a high-growth environment (ideally early-stage or startup). You're energized by helping a company find product-market fit and scale it. You've worked closely with sales, growth, or marketing teams before - and know how to translate insight into revenue. You're sharp with SQL, Python, and modern BI tools - but more importantly, you know how to ask the right questions. Bonus: you've seen zero-to-one growth before, and you're ready to do it again - faster. Why this role? You'll be one of the first data hires at a rocketship startup, with a direct line to the CEO and leadership team. Every insight you generate will inform how the company grows. You'll work in a sharp, in-person team where output matters more than credentials. Real equity. Real ownership. Real impact. We're moving fast on this one - reach out if you want to be considered.

Seeking Founding Data Scientists and Machine Learning Engineers Palladio AI | San Francisco Bay Area (Hybrid) Imagine Multiplying Your Impact You've unlocked major wins in your career - you've shipped models, moved key metrics, and proved what great data science and machine learning can do. You've bent the curve for products used by millions of people. Now, picture the idea of leveling up the entire app ecosystem by scaling your impact across many products and companies so every app in your pocket becomes smarter, more engaging, and more essential to the people who rely on it. You can help product teams iterate faster, delight users, and grow revenue, all because of the intelligence you build once and deploy everywhere. We know this ambition: we've done this again and again at places like Uber, Apple, Meta, Google, and Chime. We've had tens of billions of dollars of impact for products essential to billions of people, and we're ready to scale our impact to the next level. If this sounds like the next chapter you're looking for, read on. Why Palladio Exists Dashboards describe the past; teams need their next move . Palladio AI is the intelligence layer between raw data and decisive action, surfacing product opportunities that turn into real growth levers and guiding action so product teams iterate with confidence and velocity instead of sifting through noise. What You'll Shape Our team is building core systems in behavioral modeling, causal inference, forecasting, agentic platforms, and more. You'll help extend those domains: building ML and AI models to detect and surface product opportunities, shipping learning loops that improve themselves with every release. In short, you'll turn first-principles data science into a product that scales across industries. More than any technical challenge, you'll build a platform that helps real people make better decisions, turning data into clarity and clarity into progress. About You Craft and excellence. You dive into messy data, prototype quickly, and iterate until the insight sings. Impact mindset. 6+ years in production ML/DS; you balance scientific rigor with “it ships today, iteration on the way” pragmatism. Owner at heart. Zero-to-one energizes you; you'd rather set the standard than inherit one. Product voice. You can walk a PM through trade-offs as confidently as you tune a model. Customer-obsessed. You connect with the user's pain, measure success in user outcomes, and translate findings into product wins. Beginner's Mind. You stay hungry to learn, because better ideas are always out there. Our Team Our team has shaped the design, data, and systems behind some of the world's most iconic products. We're builders who founded Uber's Michelangelo, led data and design teams at Apple, Meta, Google, and Chime, and shipped products used by billions. We've had tens of billions of dollars of impact. Backed by top-tier investors, we're now channeling that experience into a focused, user-obsessed startup so every product team can tap the same class of intelligence at scale. Why Join Now This is the moment to have an outsized impact. You'll work directly with founders and early customers to define not just features but also the fundamental approach to how product intelligence should work. You'll see your ideas in production quickly, affecting real decisions for products used by millions. We're building a company that values clarity, craft, and impact. If those values resonate with you, we'd love to connect. Ready for the next level of impact? Reach us at ************************. Let's build breakthroughs together!

As a Senior Data Scientist, you will play a key role in empowering consumers and creating business value by designing, developing, and deploying intelligent solutions across a diverse range of clients including Financial Institutions, FinTechs, SMEs, Large Enterprises, and Government Agencies. You will focus on delivering "Certainty as a Service" through explainable and trustworthy models in domains such as lending, financial decisioning, management, and payments. Key Responsibilities: Design, develop, and deploy advanced machine learning and deep learning models for production use. Create consumable metrics, explainability frameworks, and confidence measures for decision-making solutions. Drive insights from complex and diverse datasets, including structured, unstructured, and time-series data. Work across Verification Services, Entity Resolution, Attribute & Temporal Analysis, and related platforms. Perform advanced error analysis, dimensionality reduction, and model interpretability assessments. Translate business problems into data science solutions in lending, credit scoring, and financial management. Collaborate with cross-functional teams to ensure successful deployment via Kubernetes, Docker, APIs, and event-driven architecture. Communicate findings clearly with both technical and non-technical stakeholders. Required Qualifications: Master's Degree or higher in Data Science, Computer Science, Information Systems, or a closely related field. A Ph.D. is preferred. 10+ years of commercial experience in Machine Learning / Deep Learning, including model development and deployment. Strong experience in Python for data science and software development. Solid foundation in: Natural Language Understanding (NLU). Computer Vision. Statistical Modeling Data Visualization. Classical and Advanced ML methods. Experience in model interpretability and explainability. Demonstrated ability to solve novel problems in the financial domain. Strong experience with Kubernetes, Docker, REST APIs, GraphQL, and event streaming. Excellent written and verbal communication skills. Preferred Qualifications: Exposure to credit risk modeling, risk evaluation, and financial decision systems. Experience in Finance or FinTech domains. Expertise in discrete, differential, deterministic, and probabilistic mathematical modeling. Advanced skills in Transformer models, Attention Mechanisms, PCA or other dimensionality reduction techniques. Strong background in Data Architecture, Query Optimization, and ML Ops. Familiarity with positive attribution techniques, decision science in lending, and attribute analysis.

LinkedIn is the world's largest professional network, built to help members of all backgrounds and experiences achieve more in their careers. Our vision is to create economic opportunity for every member of the global workforce. Every day our members use our products to make connections, discover opportunities, build skills and gain insights. We believe amazing things happen when we work together in an environment where everyone feels a true sense of belonging, and that what matters most in a candidate is having the skills needed to succeed. It inspires us to invest in our talent and support career growth. Join us to challenge yourself with work that matters. We work in a mission-driven organization with complex business and social models and objectives. This role will require a strong understanding of LinkedIn's business, vision and concept of labor markets; a strong ability to examine complex data and and improve the way we work. At LinkedIn, we know that labor markets matter. When publicly available data and our data are used with intention, there is significant opportunity to better understand current dynamics and trends as well as to help individuals get jobs, increase career mobility, and unlock economic opportunity. This role will be based in either Sunnyvale, San Francisco or NYC depending on which area the candidate approved-for-hire chooses. At LinkedIn, our approach to flexible work is centered on trust and optimized for culture, connection, clarity, and the evolving needs of our business. The work location of this role is hybrid, meaning it will be performed both from home and from a LinkedIn office on select days, as determined by the business needs of the team. This Role: As a Labor Economist, you will use your background in economic research and analytics to advance thought leadership about how local and global trends and shocks to the macroeconomy and labor market influence job seeking behavior and outcomes. You will partner with business leaders and employ strategic thinking to inform decisions about LinkedIn's thought leadership, product development and user experience. You'll work closely with our multi-disciplinary team of researchers to identify and conduct research that influences how we create opportunity for LinkedIn's members and create value for our customers. You will oversee research projects, working with partners across Product, Engineering, Policy, and Marketing teams. You'll develop ongoing relationships with teams to help build sustainable, long-term impact. Your work will have high visibility from leadership. Responsibilities • Conduct applied labor and macroeconomic research to generate impact for our internal and external audiences. • Design, conduct, and analyze studies with high levels of technical accuracy. • Analyze large structured and/or unstructured data. • Communicate research findings to stakeholders and leadership. • Create frameworks and tools to allow more teams across the company to leverage your research. Basic Qualifications • Masters or PhD in Economics or related field ( e.g. Business, Statistics, Engineering, other cognitive sciences) or equivalent practical experience. • 6+ years of experience network economics and research methods applied to understanding how networks impact our behavior • Experience leading research and actionable output. Preferred Qualifications • Experience in analyzing labor markets and evaluating data collected and curated from multiple sources. • Experience working with data systems, coding in SQL, R and/or Python • Excellent communication and presentation skills. Able to present complex ideas simply, directly and elicit meaningful feedback. • Demonstrated ability to frame and solve problems in an objective way, and to lead others through efficient and structured methods of decision-making. • Ability to build collaborative partnerships with Product and Engineering teams. • Experience working effectively in a highly matrixed organization that is both dynamic and high-growth. Suggested Skills • Economic Research • Data Analysis, Econometrics • Communication • Collaboration • Strategic Thinking You will Benefit from our Culture: We strongly believe in the well-being of our employees and their families. That is why we offer generous health and wellness programs and time away for employees of all levels. LinkedIn is committed to fair and equitable compensation practices. The pay range for this role is $138,000.00 to $226,000.00 Actual compensation packages are based on several factors that are unique to each candidate, including but not limited to skill set, depth of experience, certifications, and specific work location. This may be different in other locations due to differences in the cost of labor. The total compensation package for this position may also include annual performance bonus, stock, benefits and/or other applicable incentive compensation plans. For more information, visit ************************************** Equal Opportunity Statement We seek candidates with a wide range of perspectives and backgrounds and we are proud to be an equal opportunity employer. LinkedIn considers qualified applicants without regard to race, color, religion, creed, gender, national origin, age, disability, veteran status, marital status, pregnancy, sex, gender expression or identity, sexual orientation, citizenship, or any other legally protected class. LinkedIn is committed to offering an inclusive and accessible experience for all job seekers, including individuals with disabilities. Our goal is to foster an inclusive and accessible workplace where everyone has the opportunity to be successful. If you need a reasonable accommodation to search for a job opening, apply for a position, or participate in the interview process, connect with us at [email protected] and describe the specific accommodation requested for a disability-related limitation. Reasonable accommodations are modifications or adjustments to the application or hiring process that would enable you to fully participate in that process. Examples of reasonable accommodations include but are not limited to: -Documents in alternate formats or read aloud to you -Having interviews in an accessible location -Being accompanied by a service dog -Having a sign language interpreter present for the interview A request for an accommodation will be responded to within three business days. However, non-disability related requests, such as following up on an application, will not receive a response. LinkedIn will not discharge or in any other manner discriminate against employees or applicants because they have inquired about, discussed, or disclosed their own pay or the pay of another employee or applicant. However, employees who have access to the compensation information of other employees or applicants as a part of their essential job functions cannot disclose the pay of other employees or applicants to individuals who do not otherwise have access to compensation information, unless the disclosure is (a) in response to a formal complaint or charge, (b) in furtherance of an investigation, proceeding, hearing, or action, including an investigation conducted by LinkedIn, or (c) consistent with LinkedIn's legal duty to furnish information. Pay Transparency Policy Statement As a federal contractor, LinkedIn follows the Pay Transparency and non-discrimination provisions described at this link: ******************************** Global Data Privacy Notice for Job Candidates This document provides transparency around the way in which LinkedIn handles personal data of employees and job applicants: ***************************************

Data Scientist/Growth Engineer - Growth-Focused Role at a Fast-Moving AI Startup San Francisco (Onsite) | Early-stage | High ownership Our client is a fast-scaling, founder-led AI startup backed by top-tier investors. They're building a high-output engineering team and looking for a Data Scientist to help drive growth through first-principles thinking and data-led strategy. This isn't a back-office analytics role - this is about being in the room where bets are made. You'll work directly with founders to shape GTM strategy, analyze user behavior, and help define the playbook for scale. What you'll do: Analyze customer and usage data to find patterns that guide outbound, marketing, and product focus. Work hand-in-hand with the GTM team to identify high-conviction opportunities and eliminate wasted motion. Build the dashboards and reporting infra that inform the leadership team's most critical decisions. Surface actionable insights fast - even when the data is messy, incomplete, or ambiguous. Help build a data-first culture across product, growth, and execs. You might be a fit if: You've done data science or analytics in a high-growth environment (ideally early-stage or startup). You're energized by helping a company find product-market fit and scale it. You've worked closely with sales, growth, or marketing teams before - and know how to translate insight into revenue. You're sharp with SQL, Python, and modern BI tools - but more importantly, you know how to ask the right questions. Bonus: you've seen zero-to-one growth before, and you're ready to do it again - faster. Why this role? You'll be one of the first data hires at a rocketship startup, with a direct line to the CEO and leadership team. Every insight you generate will inform how the company grows. You'll work in a sharp, in-person team where output matters more than credentials. Real equity. Real ownership. Real impact. We're moving fast on this one - reach out if you want to be considered.

Seeking Founding Data Scientists and Machine Learning Engineers Palladio AI | San Francisco Bay Area (Hybrid) Imagine Multiplying Your Impact You've unlocked major wins in your career - you've shipped models, moved key metrics, and proved what great data science and machine learning can do. You've bent the curve for products used by millions of people. Now, picture the idea of leveling up the entire app ecosystem by scaling your impact across many products and companies so every app in your pocket becomes smarter, more engaging, and more essential to the people who rely on it. You can help product teams iterate faster, delight users, and grow revenue, all because of the intelligence you build once and deploy everywhere. We know this ambition: we've done this again and again at places like Uber, Apple, Meta, Google, and Chime. We've had tens of billions of dollars of impact for products essential to billions of people, and we're ready to scale our impact to the next level. If this sounds like the next chapter you're looking for, read on. Why Palladio Exists Dashboards describe the past; teams need their next move . Palladio AI is the intelligence layer between raw data and decisive action, surfacing product opportunities that turn into real growth levers and guiding action so product teams iterate with confidence and velocity instead of sifting through noise. What You'll Shape Our team is building core systems in behavioral modeling, causal inference, forecasting, agentic platforms, and more. You'll help extend those domains: building ML and AI models to detect and surface product opportunities, shipping learning loops that improve themselves with every release. In short, you'll turn first-principles data science into a product that scales across industries. More than any technical challenge, you'll build a platform that helps real people make better decisions, turning data into clarity and clarity into progress. About You Craft and excellence. You dive into messy data, prototype quickly, and iterate until the insight sings. Impact mindset. 6+ years in production ML/DS; you balance scientific rigor with “it ships today, iteration on the way” pragmatism. Owner at heart. Zero-to-one energizes you; you'd rather set the standard than inherit one. Product voice. You can walk a PM through trade-offs as confidently as you tune a model. Customer-obsessed. You connect with the user's pain, measure success in user outcomes, and translate findings into product wins. Beginner's Mind. You stay hungry to learn, because better ideas are always out there. Our Team Our team has shaped the design, data, and systems behind some of the world's most iconic products. We're builders who founded Uber's Michelangelo, led data and design teams at Apple, Meta, Google, and Chime, and shipped products used by billions. We've had tens of billions of dollars of impact. Backed by top-tier investors, we're now channeling that experience into a focused, user-obsessed startup so every product team can tap the same class of intelligence at scale. Why Join Now This is the moment to have an outsized impact. You'll work directly with founders and early customers to define not just features but also the fundamental approach to how product intelligence should work. You'll see your ideas in production quickly, affecting real decisions for products used by millions. We're building a company that values clarity, craft, and impact. If those values resonate with you, we'd love to connect. Ready for the next level of impact? Reach us at ************************. Let's build breakthroughs together!

As a Senior Data Scientist, you will play a key role in empowering consumers and creating business value by designing, developing, and deploying intelligent solutions across a diverse range of clients including Financial Institutions, FinTechs, SMEs, Large Enterprises, and Government Agencies. You will focus on delivering "Certainty as a Service" through explainable and trustworthy models in domains such as lending, financial decisioning, management, and payments. Key Responsibilities: Design, develop, and deploy advanced machine learning and deep learning models for production use. Create consumable metrics, explainability frameworks, and confidence measures for decision-making solutions. Drive insights from complex and diverse datasets, including structured, unstructured, and time-series data. Work across Verification Services, Entity Resolution, Attribute & Temporal Analysis, and related platforms. Perform advanced error analysis, dimensionality reduction, and model interpretability assessments. Translate business problems into data science solutions in lending, credit scoring, and financial management. Collaborate with cross-functional teams to ensure successful deployment via Kubernetes, Docker, APIs, and event-driven architecture. Communicate findings clearly with both technical and non-technical stakeholders. Required Qualifications: Master's Degree or higher in Data Science, Computer Science, Information Systems, or a closely related field. A Ph.D. is preferred. 10+ years of commercial experience in Machine Learning / Deep Learning, including model development and deployment. Strong experience in Python for data science and software development. Solid foundation in: Natural Language Understanding (NLU). Computer Vision. Statistical Modeling Data Visualization. Classical and Advanced ML methods. Experience in model interpretability and explainability. Demonstrated ability to solve novel problems in the financial domain. Strong experience with Kubernetes, Docker, REST APIs, GraphQL, and event streaming. Excellent written and verbal communication skills. Preferred Qualifications: Exposure to credit risk modeling, risk evaluation, and financial decision systems. Experience in Finance or FinTech domains. Expertise in discrete, differential, deterministic, and probabilistic mathematical modeling. Advanced skills in Transformer models, Attention Mechanisms, PCA or other dimensionality reduction techniques. Strong background in Data Architecture, Query Optimization, and ML Ops. Familiarity with positive attribution techniques, decision science in lending, and attribute analysis.