Product Data Scientist

About the role

Join Clair as a Product Data Scientist, where you'll own the experimentation and analytics layer that drives product and underwriting decisions. You'll design experiments, define success metrics, and translate data into actionable product strategy. This role requires strong business intuition, deep expertise in experimentation and statistics, and the ability to translate complex data into clear strategic recommendations. Key missions: Own and manage Clair’s experimentation ecosystem, including the design, execution, and analysis of A/B tests across underwriting and product experiences.. Translate model outputs (e.g., risk scores) into actionable business decisions, such as approval thresholds and lending strategies.. Define and standardize core product and financial metrics, including how we measure model impact, user behavior, and unit economics. Profile: - We’re looking for someone with strong business intuition, deep expertise in experimentation and statistics, and the ability to translate complex data into clear strategic recommendations - Proven experience owning end-to-end experimentation programs and influencing product decisions through data - Strong business intuition and ability to think in terms of trade-offs, unit economics, and growth vs. risk - Strong SQL skills and experience working with large datasets - 5+ years of experience in data science, product analytics, or a related analytical role - Experience working cross-functionally with Product, Finance, or Strategy teams in a fast-paced environment - Demonstrated ability to translate complex analyses into clear business insights and recommendations - Strong foundation in statistics and experimental design, including A/B testing, causal inference, and hypothesis testing - Experience in fintech, lending, or credit-related products - Experience building forecasting models for business or financial metrics - Familiarity with underwriting concepts such as risk scoring, approval strategies, and loss modeling - Proficiency in Python or R for data analysis - Experience with experimentation platforms and statistical tooling