Senior Data Scientist, Organic Growth

About the role

We are hiring a Sr. Data Scientist, Organic Growth to help us understand how our investment in search, app store, and content surfaces drives member acquisition and long-term value. Unlike paid channels, organic growth compounds over time, is mediated by ranking algorithms we don't control, and carries no click-level cost signal — requiring a distinct measurement lens that accounts for paid–organic cannibalization, branded vs. non-branded intent, lagged and compounding returns, and the self-selected high intent of organic traffic.

As our Sr. Data Scientist, Organic Growth, you will partner closely with the Organic Growth team to measure, optimize, and scale investment across SEO, ASO, and content. You will bring expertise in opportunity sizing, operational planning, and channel forecasting, helping the team plan confidently and allocate resources — content production, technical engineering work, and app store optimization — effectively. You will bring rigor to how we evaluate incrementality, attribution, and efficiency, moving us to a defensible view of what our organic investment actually delivers.

The base salary offered for this role and level of experience will begin at $133,000 and up to $185,000. Full-time employees are also eligible for a bonus, competitive equity package, and benefits. The actual base salary offered may be higher, depending on your location, skills, qualifications, and experience.

In this role, you can expect to

• Partner with Organic Growth to define KPIs and measurement frameworks across surfaces — SEO landing pages, content hubs, app store listings — and audiences
• Size and scope organic growth initiatives in partnership with marketing, product, engineering, and finance: translating acquisition goals into expected traffic, conversion, and member volume, and the investment required to get there, while supporting operational planning for content and technical roadmaps
• Build and maintain forecasting models for the organic channel, projecting impressions, sessions, install and signup volume, and downstream LTV under different investment scenarios, seasonality assumptions, ranking trajectories, and algorithm volatility
• Develop attribution approaches that reconcile platform-reported performance (Google Search Console, App Store Connect, Google Play Console, web and app analytics) with observed member behavior, accounting for dark and direct traffic, branded vs. non-branded intent, and paid–organic overlap
• Design and analyze SEO split tests, app store listing experiments (Google Play Experiments, Apple Product Page Optimization), geo experiments, and paid search holdouts to quantify incremental lift, cannibalization, and true impact vs. correlation
• Build and maintain dashboards that give clear visibility into rankings and impression share, traffic, funnel conversion, blended CAC, and downs