Senior Data Scientist, Referrals
$133,000–$133,000 year
HybridSan Francisco, California, United States
San Francisco, California, United StatesHybridFull Time$133,000–$133,000 yearSenior LevelDoctorate Or Professional DegreeFintechLarge
Full TimeSenior LevelDoctorate Or Professional DegreeLargeFintech
Job Summary
Partner with the Referrals team to define KPIs, measure incrementality, and build forecasting models for campaign sizing and ROI projections. Size referral campaigns by translating acquisition goals into expected spend and volume, then design geo experiments and holdouts to quantify true impact. Develop attribution approaches that reconcile platform data with observed member behavior, while maintaining dashboards for spend, CAC, and downstream LTV. Collaborate with Data Engineering to improve tracking pipelines and translate complex analyses into actionable recommendations for leadership.
Required Qualifications
- 4+ years of experience in referral programs and in marketing, growth, or product analytics
- Experience in FinTech
- Experience with marketing campaign planning and sizing: comfortable working from business goals backward to estimate required spend, expected member volumes, and unit economics, with an understanding of how campaigns are operationally structured and executed
- Forecasting experience for a marketing or growth channel: building models that project forward-looking performance and communicating forecast uncertainty and scenario sensitivity to cross-functional stakeholders
- Strong experience designing and evaluating incrementality tests: geo experiments, holdouts, and platform lift studies
- Working knowledge of causal inference methods including experiment design, holdout analysis, and techniques for isolating organic from incentive driven behavior
- Advanced SQL skills and proficiency in Python or R for analysis and modeling
- Experience building dashboards (e.g., Looker, Tableau, or similar BI tools) that drive stakeholder decision-making
- A strong understanding of attribution concepts and the challenges of measurement in a privacy-constrained, cross-device environment
- The ability to communicate complex findings clearly to both technical and non-technical partners and influence decisions with data
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