Data Scientist - Analytics - local to SF Bay Area, CA

Our client, a leader in fintech, is seeking a contract Data Scientist. This is s hybrid role Tue - Thu onsite in San Francisco. The rest is remote

contract duration - 6 months + extensions (possible C-H)

Product Data Scientist, Lending

About the Role

as a data scientist, must be strong in SQL and Python - to build and deploy ML models - risk models, churn, models, response models - advanced data analytics

Join a growing product team focused on data-driven decision-making and innovation in lending. As Product Data Scientist, you will serve as the embedded analytics and experimentation expert, shaping and growing a core lending product. You’ll drive analytics, run experiments, build models, and translate data into insights for the team, partnering closely with product, engineering, and business stakeholders.

Key Responsibilities

• Act as the analytics/data science point of contact for Product Managers, turning ambiguous questions into clear analyses and actionable recommendations.
• Design, execute, and interpret A/B and quasi-experimental tests throughout the borrower funnel, ensuring rigor in metrics and test setup.
• Develop, define, and own product metrics, funnel and cohort definitions, and ensure robust event instrumentation with engineering.
• Build and maintain data pipelines, transformations, and feature models for ongoing analysis.
• Develop and validate statistical and machine learning models (response propensity, conversion, segmentation, risk/pricing signals) with a focus on fairness and explainability.
• Apply Model Context Protocol (MCP) standards to ensure transparency, context-awareness, and regulatory compliance in model development, deployment, and monitoring.
• Use AI tooling to accelerate analysis and documentation while applying human judgment before making recommendations.
• Communicate results via clear write-ups, visuals, and product-focused recommendations.
• Contribute to roadmap and planning discussions with opportunity sizing, measurement risk identification, and ongoing experiment monitoring.

• About You
• 5+ years’ experience in analytics/data science roles directly informing product decisions; bachelor’s degree or higher in a quantitative field (or equivalent experience).
• Strong background in statistics and experimentation (hypothesis testing, causal inference, design), able to explain and apply meaningful metrics.
• Fluent in SQL and at least one scripting/statistical language (Python or R); comfortable with data engineering and pipeline development.
• Skilled at building and evaluating statistical/ML models, balancing complexity and practicality.
• Experience implementing or operationalizing Model Context Protocol (MCP) or similar standards for model governance, context-awareness, and compliance is a plus.
• Confident user of AI/LLM tools for analysis, documentation, and workflow acceleration.
• Strong critical thinking, with a consultative approach to problem-solving and stakeholder management.
• High standards for measurement accuracy; able to flex communication to technical and non-technical audiences.

• Nice to Have
• Experience in fintech, consumer lending, or related financial services
• Familiarity with CDP platforms, event instrumentation, or experimentation tools
• Direct experience with credit or risk modeling, pricing, or marketing decisioning
• Hands-on with dbt, Airflow, or similar data pipeline/orchestration tools
• Prior experience embedded with product teams in agile environments