Senior Data Scientist, Organic Growth

Chime Financial, Inc•San Francisco, CA

6h•$133,000 - $185,000•Hybrid

About The Position

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.

Requirements

5+ years of experience in organic growth channels (SEO, ASO, content) and in marketing, growth, or product analytics. Experience in FinTech preferred.
Experience with organic growth planning and opportunity sizing: comfortable working from business goals backward to estimate required investment, expected traffic and member volumes, and unit economics, with an understanding of how content and technical SEO/ASO work is 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: SEO split tests, app store listing experiments, geo experiments, and paid holdouts
Working knowledge of causal inference methods including experiment design, holdout analysis, and techniques for separating incremental organic demand from cannibalized paid or brand-driven demand
Advanced SQL skills and proficiency in Python or R for analysis and modeling
Experience working with organic platform data sources (Google Search Console, App Store Connect, Google Play Console, third-party rank tracking or crawl tools)
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

Responsibilities

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 downstream LTV by surface, keyword cluster, and content type
Collaborate with Data Engineering to improve tracking, data quality, and the pipelines behind crawl, ranking, session, and conversion data
Translate complex analyses into clear, actionable recommendations for cross-functional leadership