Marketing Data Scientist

SoFi•San Francisco, CA

5h•$105,600 - $198,000

About The Position

SoFi is seeking a highly motivated Data Scientist to join the Marketing Data Science (MDS) team. The MDS team plays a crucial role in enabling data-driven decisions across SoFi's Marketing organization through robust analytics, modeling, experimentation, and measurement. This role will support Lifecycle Marketing (LCM) data enablement - building the reporting, tooling, and self-serve foundations that help LCM leads plan, execute, and measure member communications. The work includes improving data reliability, partnering with Engineering on data products, enabling AI-assisted self-serve analytics, and supporting incrementality measurement so the team can distinguish true campaign lift from correlational reporting. The position will report to a Staff Marketing Data Scientist and partner day-to-day with a Senior Marketing Data Scientist who oversees LCM lead communication and project management. You will focus on execution, implementation, and day-to-day reliability of LCM reporting and tooling. This role is ideal for someone who enjoys building high-quality data products, working with both technical and marketing partners, and growing toward greater ownership over time.

Requirements

Bachelor’s degree in Computer Science, Mathematics, Statistics, Engineering, or a related quantitative field.
2+ years of experience in data science, analytics, or data engineering roles supporting marketing, lifecycle/CRM, communications, growth, or product analytics.
Strong proficiency in SQL and working knowledge of Python for data analysis and pipeline development.
Experience building or maintaining dashboards and self-serve reporting solutions (e.g., Tableau or similar BI tools); interest in AI-assisted self-serve analytics is a plus.
Familiarity with modern data stacks and workflow tools such as dbt, Airflow, and cloud data warehouses (e.g., Snowflake), or a strong willingness to learn.
Experience working with structured datasets and applying consistent business logic across reporting outputs; familiarity with marketing communications or CRM data is a plus.
Experience with incrementality measurement (e.g., holdouts, A/B tests, or other causal methods) is preferred.
Ability to follow established standards while contributing thoughtful improvements to data quality, efficiency, and maintainability.
Strong attention to detail and comfort working with operational data that requires high accuracy.
Clear communication skills and the ability to collaborate effectively with cross-functional, non-technical partners.
Curiosity, reliability, and a growth mindset, with interest in developing toward greater ownership over time.

Nice To Haves

Interest in AI-assisted self-serve analytics is a plus.
Familiarity with modern data stacks and workflow tools such as dbt, Airflow, and cloud data warehouses (e.g., Snowflake), or a strong willingness to learn.
Familiarity with marketing communications or CRM data is a plus.
Experience with incrementality measurement (e.g., holdouts, A/B tests, or other causal methods) is preferred.

Responsibilities

Build and maintain automated reporting pipelines, dashboards, and datasets that support Lifecycle Marketing performance
Improve LCM data foundations by implementing standardized logic, definitions, and quality checks across communications channels (e.g., email, push, in-app, and related CRM activity).
Develop and enhance self-serve reporting and AI-assisted analytics tooling so LCM stakeholders can monitor performance and answer routine questions independently.
Investigate and help resolve data discrepancies, delays, or pipeline issues affecting LCM reporting and campaign measurement.
Partner with Engineering and Marketing Data Science to productionize data products, automate recurring workflows, and improve reliability of LCM datasets.
Support time-sensitive stakeholder requests by extending existing reporting frameworks rather than creating one-off, unmaintainable analyses.
Contribute to documentation of data definitions, business logic, and reporting processes so LCM leads and MDS partners can work from a shared source of truth.
Support incrementally measurement for lifecycle campaigns, including holdout and experiment design, analysis, and translating lift results into recommendations for stakeholders.
Collaborate with LCM, Product, Engineering, and MDS partners to gather requirements, validate outputs, and translate findings into clear, actionable insights.