Data Scientist, Member Insights - Subscriptions CA - San Francisco; WA - Seattle

Position: Staff Data Scientist, Member Insights - Subscriptions CA - San Francisco; WA - Seattle

Staff Data Scientist, Member Insights - Subscriptions

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 are looking for a highly strategic and technically strong Staff Data Scientist to join the Member Data Science team, focused on driving engagement and long-term member value, specifically for our subscription premium program, SoFi Plus. This role will be responsible for deeply understanding the drivers of engagement, retention, and subscription value across the SoFi ecosystem. You will define and own engagement measurement frameworks, lead high-impact analytical deep dives, design causal experiments, and develop scalable data and modeling solutions that inform product strategy for SoFi Plus.

The Member Organization builds engaging and personalized experiences for our members across our product lines. As a Staff Data Scientist, you will operate as a data thought partner to Product, Engineering, Lifecycle Marketing, and Leadership. You will shape the engagement roadmap through insights on activation, feature adoption, habit formation, churn risk, subscription upgrades/downgrades, and long-term member value. You will proactively identify the most impactful opportunities to improve subscription engagement and revenue, and ensure we are making disciplined, data-informed investment decisions.

This role requires strong technical skills (SQL, Python/R, Tableau, Statistics), deep expertise in metrics, segmentation, A/B testing, and strong collaboration.

This is a highly cross-functional and high-visibility role with direct impact on member experience and recurring revenue growth. This is an exciting role for someone to make a direct impact on the company's growth trajectory and member experience.

Responsibilities:

• Design and implement data collection and processing pipelines
• Develop and apply machine learning models to solve business problems. Translate modeling outputs into actionable business strategies.
• 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
• Proven experience building scalable dashboards and executive-ready reports that measure product performance, subscription health, and engagement KPIs, and effectively translate insights into actionable business recommendations.
• Experience with leveraging LLMs or other AI solutions to develop analytical tools.

Qualifications:

• Master’s degree or higher in Statistics, Economics, Applied Mathematics, Computer Science, Engineering, or related quantitative field.
• 7+ years of experience leveraging data-driven analysis to influence product and business strategy, ideally in a tech or subscription-based company.
• Deep expertise in:
• Retention and engagement analytics
• Cohort and lifecycle analysis
• Subscription metrics (churn, LTV, ARPU)
• Experimental design and causal inference
• Strong proficiency in SQL, experience with visualization tools (e.g., Tableau) and python.
• Experience building data pipelines using DBT and orchestrating workflows with Airflow in Snowflake environments.
• Proven experience developing and deploying machine learning models in production with monitoring frameworks.
• Strong understanding of subscription economics and revenue optimization.
• Demonstrated ability to work independently in ambiguous environments and drive measurable business impact.
• Excellent communication skills, including the…