Mochi Health is looking for a Senior Data Scientist to design, run, and interpret experiments to understand what works and what doesn't in their telehealth platform for weight loss, driving evidence-based decision-making and improving patient experience and company growth.
Requirements
- 4+ years of industry experience in applied experimentation (growth or product preferred)
- Deep expertise in causal inference methods (A/B testing, DiD, matching, Bayesian methods)
- Strong Python and SQL skills; capable of building reusable frameworks, not just one-off analyses
Responsibilities
- Own the design and execution of experiments (A/B tests, quasi-experiments) across pharmacy, design, and product flows
- Partner with design and pharmacy teams to ideate, prioritize, and scope impactful experiments
- Build frameworks and tools to standardize experimentation and causal inference across teams
- Ensure experiment integrity—sample sizing, randomization, stopping rules, multiple-testing corrections
- Move beyond binary “did it win?” to nuanced insights: heterogeneous treatment effects, and trade-offs
- Automate experiment reporting and integrate results into dashboards / internal tools
- Mentor teammates and set best practices for experimentation at the company
Other
- Full-time / Onsite (5 days/week)
- Clear communicator who can translate complex experimental results into actionable recommendations
- Comfortable with ambiguity, fast iteration, and working across very different teams (Example: pharmacy, design, ops)
- Motivated by impact - you want your work to directly shape patient care and company growth
- Bachelor’s or Master’s in a quantitative field (e.g., Statistics, Engineering, Economics)
