Senior Data Scientist, Member Insights - Growth

SoFi•Seattle, WA

About The Position

Shape a brighter financial future with us. Together with our members, we’re changing the way people think about and interact with personal finance. We’re a next-generation financial services company and national bank using innovative, mobile-first technology to help our millions of members reach their goals. The industry is going through an unprecedented transformation, and we’re at the forefront. We’re proud to come to work every day knowing that what we do has a direct impact on people’s lives, with our core values guiding us every step of the way. Join us to invest in yourself, your career, and the financial world. We’re looking for a highly skilled Senior Data Scientist to play a pivotal role on the Member Data Science team, focused on driving and accelerating member growth across a broad set of member growth initiatives. This role will be instrumental in establishing measurement frameworks and analytical infrastructure to support growth strategies end to end. Key responsibilities include defining success metrics, building tracking systems, designing experiments, conducting customer segmentation and price elasticity analyses, and optimizing member acquisition economics with propensity models. The Member Organization builds engaging and personalized experiences for our members across our product lines. As a Sr. Data Scientist on the Member Growth pillar, you will be responsible for defining and owning core growth KPIs, building and maintaining reliable dashboards and reporting to track performance, and establishing clear success metrics across the growth funnel. You will conduct deep-dive analyses such as customer segmentation, funnel analysis, A/B testing, and elasticity or trade-off evaluations to identify levers that optimize conversion, and become an SME in our member referral program. You will develop models (e.g., propensity or uplift models) to inform targeting, prioritization, and investment decisions across growth initiatives. This role requires strong technical skills (SQL, Python/R, Tableau, Statistics), deep expertise in metrics, segmentation, experimentation, and strong collaboration. This role is inherently cross-functional, you will work closely with engineering, product managers, lifecycle marketing, data science, design, operations, finance, and executive teams to set growth objectives, define referral program strategy, prioritize features, provide insights, and execute on them. This is an exciting role for someone to make a direct impact on the company's growth trajectory and member experience.

Requirements

Bachelor’s degree required (Master’s preferred) in Computer Science, Math, Physics, Engineering or quantitative field.
4+ years of relevant work experience
Strong programming skills in SQL, Python/R and proficiency in Tableau
Proven experience creating dashboards and reports that drive business decisions
Experience with using DBT, Airflow to build Data Pipelines in Snowflake
Experience with experimental design/interpretation, A/B testing, quasi-experimentation for causal inference
Experience with data mining, descriptive analytics, defining KPIs, machine learning, statistical modeling, and predictive modeling concepts.
Experience with funnel analysis, cohort analysis, and segmentation
Demonstrate strong business acumen and curiosity, with excellent communication and presentation skills, including the ability to present to leadership.
Ability to work independently and as part of a team. You should be able to initiate and drive projects to completion
Exceptional problem-solving skills
Influence outcomes and communicate technical content to general audiences
Work independently in a dynamic, cross-functional environment, with strong attention to detail and the ability to be a team player.
Prepare comprehensive data reports and make insights easy to understand.

Responsibilities

Design and implement data collection and processing pipelines
Develop and apply machine learning models to solve business problems
Strong experience owning product analytics workflows including formulating success metrics, socializing them across the organization, and creating dashboards/reports
Evaluate and interpret the results of data analysis
Communicate findings to influence technical and non-technical stakeholders
Stay up-to-date on the latest data science techniques and technologies
Build data pipelines to deploy production level datasets

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