Senior Data Scientist, Growth Marketing & Experimentation

Rocket Money; Phoenix (AZ); On-site; USD 180,000 - 235,000; Full time

Benefits offered by this job

Life Insurance

Disability benefits

401k Matching

Stock Purchase Program

Tuition Reimbursement

Unlimited PTO

Daily Lunch & Coffee

Commuter benefits

Competitive Pay

Job summary

Rocket Money is seeking a Senior Data Scientist to drive marketing efficiency, attribution, and experimentation across our fintech offerings. You will build customer lifetime value models, implement media mix attribution, and design causal impact assessments to optimize marketing strategy.

You will lead product scientific experimentation programs, build scalable tooling for self-service experiments, and mentor teammates while collaborating with engineering and product teams.

Qualifications

• 6+ years of professional data science experience.
• Proficiency in SQL and at least one scripting language.
• Experience with statistical modeling and causal inference.
• Experience building production-grade tooling for experimentation.
• Strong communication and cross-functional collaboration.

Responsibilities

• Build customer lifetime value models and integrate into marketing decisions.
• Lead marketing effectiveness measurement and estimation approaches.
• Design and conduct experiments to estimate impact of strategies.
• Work with data engineering to build scalable ML pipelines for experimentation.
• Mentor teammates and maintain high technical standards.
• Collaborate with product and engineering to deploy predictive tools.

Skills

SQL

Scripting language

Statistical modeling

Experimentation platforms

Marketing analytics

Job description

Rocket Money is seeking a Senior Data Scientist to drive marketing efficiency, attribution, and experimentation across our fintech offerings. You will build customer lifetime value models, implement media mix attribution, and design causal impact assessments to optimize marketing strategy.

You will lead product scientific experimentation programs, build scalable tooling for self-service experiments, and mentor teammates while collaborating with engineering and product teams.