Data Scientist

Rocket Money
Washington, DC, United States
8 days ago

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
6 years minimum
Compensation
$180,000.0 - $235,000.0
Working hours
Regular working hours

Tech stack

A/B Testing Data Analysis Code Review Data Cleansing Information Engineering Design of User Interfaces Human-Computer Interaction Statistical Hypothesis Testing Machine Learning Systems Development Life Cycle SQL Databases Systems Architecture
+3 more
Scripting Data Analytics Data Management

Job description

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.

  • 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. *, A/B Testing, Analysis Skills, Banking Services, Code Reviews, Communication Skills, Cross-Functional, Customer Acquisition, Customer Relations, Customer Relationship Management (CRM), Customer Support/Service, Data Analysis, Data Management, Data Modeling, Data Science, Dental Insurance, Documentation, Experiment Design, Finance, LifeTime Value (LTV), Machine Learning, Machine Tool, Market Segmentation, Marketing, Marketing Strategy, Mentoring, Onboarding, Problem Solving Skills, Process Improvement, Product Development, Product Engineering, Product Programs, Product Strategy, Production Systems, Publications, Purchasing/Procurement, Relationship Marketing, SQL (Structured Query Language), Scalable System Development, Scripting (Scripting Languages), Statistical Modeling, Strategic Analysis, System Architecture, Team Player, Technical Marketing, Test Design, Testing, Time Management, Tuition Reimbursement, User Interface/Experience (UI/UX), Vision Plan, Writing Skills

Benefits & conditions

  • 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.

Rocket Money is an Affirmative Action and Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, or protected veteran status and will not be discriminated against on the basis of disability.

Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.

Apply for this position

This job is hosted externally. Click below to view the full posting and apply.

Apply on www.careerbuilder.com

Good distractions

Talks and stories from around this role — technically off-topic, practically not.

1:04 min

Introduction to Bitcoin script parsing tools

Steve Shadders · LIVE

54 sec

Generating multiple hook options for outreach A/B testing

Leandro Gomes da Silva Leandro Gomes da Silva · WWC 2025

3:39 min

Addressing code review surrender and process exploitation

Laura Tacho Laura Tacho · WWC Europe 2026

3:09 min

Balancing data science skillings alongside systems engineering rigor

Nico Schmidt · LIVE

1:53 min

Evaluating traditional scripting languages for modern development tasks

Jens Knipper Jens Knipper · Europe 2026 Virtual

3:23 min

Exploring specialized career paths within the data science ecosystem

Julian Joseph · LIVE

Videos

See all

Related articles

See all