Senior Data Scientist, Growth Marketing

ABOUT ROCKET MONEY🔮 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. ABOUT THE TEAM 🤹 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. ABOUT THE ROLE 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. 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. Support 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 stakeholders to implement operational change. Design and conduct experiments to estim ate 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.