Senior Data Scientist, Growth Marketing at Rocket Money in San Francisco, CA, Washington, D.C., New York City, NY, Detroit, MI, Phoenix, AZ, Miami, FL, Denver, CO.

Job description

• 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.

Responsibilities

• 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 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.

Requirements

• 6+ years of professional experience in data science, with proficiency in SQL, at least one scripting language, statistical modeling, and engineering scalable experimentation solutions.
• You have direct experience building production grade tooling for operational use by teams of internal decision makers. You know how to drive marketing and product strategy with experimental and observational data and build the tools that can implement it at the tactical level.
• You’ve worked with engineering teams to design optimal feedback signals between applications and ad networks or build experimentation platforms.
• You are a team player with a proven ability to collaborate across teams and communicate technical insights effectively, driving alignment with marketing strategy and operations.
• You care about problems, not publications. Solving business problems is your primary goal. We love recovering academics that aren’t looking in the rearview.
• You care just as much about why you're solving a problem as the solution. You always want a deep understanding of context and business impact. You are a data scientist first but an expert analyst when necessary.
• Excellent writing, presentation, and communication skills. Documenting, soliciting feedback, and securing alignment among collaborators is second nature.
• Deep experience in several of the following in a professional capacity: customer segmentation, customer lifetime value modeling, A/B testing and causal inference, media mix modeling.
• Experience in fintech, banking, or finance is a plus.

Skills

Required

• SQL
• At least one scripting language
• Statistical modeling
• Building production grade tooling
• Experimental design and assessment
• Causal inference
• A/B testing
• Customer segmentation
• Customer lifetime value modeling
• Media mix modeling

Benefits

• Health, Dental & Vision Plans
• Life Insurance
• Long/Short Term Disability
• Competitive Pay
• 401k Matching
• Team Member Stock Purchasing Program (TMSPP)
• Learning & Development Opportunities
• Tuition Reimbursement
• Unlimited PTO
• Daily Lunch, Snacks & Coffee (in-office only)
• Commuter benefits (in-office only)
• Additional information: Salary range of $180,000 - $235,000/year + bonus + benefits. Base pay offered may vary depending on job-related knowledge, skills, and experience.