Product Data Scientist

Location: San Francisco, CA | Work Arrangement: Hybrid (3 days onsite / 2 days WFH) | Experience Required: 5+ years | Industry: Banking / Financial Services | Duration: Long‑Term Contract | Engagement: C2C Contractual Basis

Responsibilities

• Partner with Product Managers to turn business questions into actionable analysis.
• Design, execute, and interpret A/B and quasi‑experiments.
• Define product metrics, funnels, cohorts, and measurement frameworks.
• Build and maintain SQL/dbt data models and pipelines.
• Develop statistical and machine‑learning models supporting product, credit, pricing, and conversion decisions.
• Work with Engineering on event tracking and instrumentation.
• Monitor product and experiment performance and identify anomalies and opportunities.
• Communicate findings and recommendations to technical and executive stakeholders.
• Support product roadmap and planning through data‑driven insights.

Requirements

• 5+ years of experience in Data Science, Product Analytics, Applied Statistics, or Analytics Consulting.
• Banking / Financial Services experience required.
• Consumer lending, fintech, credit, or home improvement financing experience preferred.
• Strong SQL and Python or R skills.
• Strong knowledge of A/B testing, experimentation, hypothesis testing, and causal inference.
• Experience with product analytics, funnel analysis, cohort analysis, and metrics frameworks.
• Statistical and Machine Learning modeling experience.
• Experience with dbt, Airflow, or similar data pipeline tools is a plus.
• Knowledge of credit/risk modeling, pricing, underwriting, or loan origination is highly desirable.
• Experience with product instrumentation tools such as Segment, mParticle, or Amplitude is a plus.
• Strong communication skills with Product, Engineering, and Business stakeholders.
• Experience using AI/LLM tools for analytics and documentation is a plus.

Education

Bachelor’s degree or higher in a quantitative field such as Statistics, Mathematics, Economics, Computer Science, Data Science, Finance, or equivalent experience.