Senior Data Scientist, Decisions

The ideal candidate is local to and interested in working from any of our offices (Silver Spring, NYC, SF, Miami, Denver) 1-2x per week.

Rocket Money’s mission is to meaningfully improve the financial prosperity of millions of people. Rocket Money offers members a unique understanding of their finances and a suite of valuable services that save them time and money – ultimately giving them a leg up on their financial journey.

Data Scientists at Rocket Money advance our mission by building internal and external products that strengthen customer relationships across our financial offerings. We work closely with product and engineering teams to test the effectiveness of features that help customers understand, track, and improve their personal finances. Data Scientists also enhance growth operations through ML-powered personalization during onboarding, modeling customer lifetime value, and estimating the relationship between marketing operations and user acquisition outcomes.

We seek team players who excel at cross-team collaboration, use data to shape strategy, and deliver solutions effectively within cross-functional teams. While Data Scientists primarily focus on model development, data preparation, and experimental testing + design, they also contribute to system architecture, design, deployment, and evaluation.

Rocket Money is looking for a Senior Data Scientist to drive marketing efficiency, attribution, and experimentation efforts through the use of tools like customer lifetime value modeling, media mix attribution modeling, and causal impact assessments of marketing strategies. This role will also lead product scientific experimentation program efforts, including building tooling and processes for self‑service product and CRM experimentation.

• Lead internal marketing effectiveness measurement and estimation approaches.
• Be responsible for leading projects from start to finish — making key decisions on both implementation and scope while balancing technical and business goals and working with stakeholders to implement operational change.
• Design and conduct experiments to estimate the impact of marketing and product strategies. Create scale by leading a systematic marketing and product experimentation program. Contribute to product experimentation via expert level experimental design, assessment, and collaboration with product managers.
• Work with data engineering and analytics teams to build scalable and durable machine learning to data analytics pipelines that enable marketing and product experimentation operations.
• Optimize to continuous product feedback loops — you understand that data product development is the practice of a continuous lifecycle of measurement, analysis, modeling, and hypothesis testing. You understand how to build, test, and deliver internal facing predictive tools. You understand how to effectively design and assess experiments for a variety of user facing experiences.
• Maintain a high technical bar by mentoring other members, participating in code reviews, and ensuring quality in production systems. Level up others around you via effective technical mentoring.
• Work with engineering teams to design and architect predictive feedback mechanisms for digital ad networks and add new features to our in‑house experimentation engine.
• Be on the cusp of new developments in marketing data science tech and drive operational changes in marketing that are cutting edge.
• Create scalable approaches and tooling that allow others on the data team to undertake product experimentation without your direct input.

In this role, you will focus on the following types of problems:

• Collaborate closely with Product, Marketing, and Engineering teams to define marketing measurement and optimization strategy and build internal predictive tools.
• Build the next generation of Rocket Money’s customer lifetime value models and integrate into the operational decision making and optimization of our marketing portfolio.
• Level up our product experimentation program. Rigorously design experiments to assess the effectiveness of product experiences. Reassess baseline approaches…