Senior Data Scientist, Referrals
This role measures and forecasts referral-channel performance, develops attribution and incrementality frameworks, and guides campaign investment through experimentation, modeling, and dashboards. It requires 4+ years in referral, marketing, growth, or product analytics, advanced SQL, Python or R, and strong causal analysis experience.
About the job
Responsibilities
- Partner with the Referrals team to define KPIs and measurement frameworks across campaigns and audiences.
- Size and scope referral campaigns with marketing, product, and finance by translating acquisition goals into expected spend, volume, and ROI projections.
- Build and maintain forecasting models for referral-channel acquisition volume, cost, and downstream LTV across spend scenarios, seasonality assumptions, and campaign configurations.
- Develop attribution approaches that reconcile platform-reported performance with observed member behavior, including dual-sided incentives and organic word-of-mouth overlap.
- Design and analyze geo experiments, holdouts, and platform lift studies to quantify incremental lift.
- Build and maintain dashboards covering spend, CAC, funnel conversion, and downstream LTV by campaign.
- Collaborate with Data Engineering to improve tracking, data quality, and pipelines for spend, click, and conversion data.
- Translate complex analyses into actionable recommendations for cross-functional leadership.
Requirements
- 4+ years of experience in referral programs and in marketing, growth, or product analytics.
- Experience with marketing campaign planning and sizing, including estimating spend, member volumes, and unit economics.
- Experience forecasting performance for a marketing or growth channel and communicating uncertainty and scenario sensitivity.
- Strong experience designing and evaluating incrementality tests, including geo experiments, holdouts, and platform lift studies.
- Working knowledge of causal inference methods, experiment design, holdout analysis, and isolating organic from incentive-driven behavior.
- Advanced SQL skills and proficiency in Python or R for analysis and modeling.
- Experience building dashboards with Looker, Tableau, or similar BI tools.
- Understanding of attribution and measurement challenges in privacy-constrained, cross-device environments.
- Ability to communicate complex findings clearly to technical and non-technical partners and influence decisions with data.
Nice to Have
- FinTech experience.
Compensation and Benefits
- Base salary: $133,000–$185,000.
- Eligibility for a bonus, competitive equity package, and benefits.
- Comprehensive health, financial, and wellbeing benefits.
- Backup child, elder, and pet care; subsidized commuter benefits for eligible employees.
- Generous vacation policy and company-wide paid days off.
- Annual wellness stipend.
- Paid parental leave and family planning reimbursement.
Skills
SQL, Python, R, Looker, Tableau, Causal Inference, Experiment Design, Holdout Analysis, Attribution, Forecasting, Dashboarding, Ltv Modeling
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