Data Scientist- Customer Lifecycle and Engagement

Join a leading fintech company that’s democratizing finance for all.

Robinhood Markets was founded on a simple idea: that our financial markets should be accessible to all. With customers at the heart of our decisions, Robinhood and its subsidiaries and affiliates are lowering barriers and providing greater access to financial information. Together, we are building products and services that help create a financial system everyone can participate in.

With growth as the top priority...

The business is seeking curious, growth-minded thinkers to help shape our vision, structures and systems; playing a key-role as we launch into our ambitious future. If you’re invigorated by our mission, values, and drive to change the world — we’d love to have you apply.

About the team + role

The Marketing Data Science team plays a critical role in shaping how Robinhood engages with current and prospective customers. As a Senior Data Scientist, you’ll focus on improving how marketing communications are ranked and prioritized—ensuring the right message reaches the right user at the right time. This role partners closely with Marketing, Growth, Engineering, and Machine Learning teams to enhance engagement, boost conversion rates, and elevate the user experience through data-driven strategies.

The role is located in the office location(s) listed on this job description which will align with our in-office working environment. Please connect with your recruiter for more information regarding our in-office philosophy and expectations

What You’ll Do

In this role, you’ll collaborate with cross-functional teams to design and analyze experiments—including A/B tests and quasi-experiments—to evaluate the impact of marketing initiatives. You’ll build and refine predictive models and customer segmentation strategies to anticipate user behavior and optimize engagement. You’ll also develop scalable data pipelines and dynamic dashboards that deliver real-time insights, supporting decision-making across Marketing, Product, Engineering, and Finance.

What You Bring

• Predictive Modeling & ML Expertise: Experience developing and deploying supervised and unsupervised machine learning models (e.g., regression, classification, clustering) to forecast user behavior and optimize marketing interventions.
• Customer Segmentation: Proficiency in segmenting users based on behavioral and demographic data, leveraging techniques like clustering and propensity scoring to inform targeted strategies.
• Experimentation & Causal Inference: Hands-on experience designing and analyzing A/B tests, quasi-experiments, and applying basic causal inference techniques to determine the true impact of initiatives.
• Technical Proficiency: Strong skills in Python, SQL, and data visualization tools, with experience in building automated data pipelines and dashboards.
• Analytical Communication: Ability to translate complex data insights into clear, actionable recommendations for cross-functional teams, ensuring our data drives effective decision-making.

What we offer

• Market competitive and pay equity-focused compensation structure
• 100% paid health insurance for employees with 90% coverage for dependents
• Annual lifestyle wallet for personal wellness, learning and development, and more!
• Lifetime maximum benefit for family forming and fertility benefits
• Dedicated mental health support for employees and eligible dependents
• Generous time away including company holidays, paid time off, sick time, parental leave, and more!
• Lively office environment with catered meals, fully stocked kitchens, and geo-specific commuter benefits

We use Covey as part of our hiring and / or promotional process for jobs in NYC and certain features may qualify it as an AEDT. As part of the evaluation process we provide Covey with job requirements and candidate submitted applications. We began using Covey Scout for Inbound on September 19, 2024.

Please see the independent bias audit report covering our use of Covey here.

Base pay for the successful applicant will depend on a variety of job-related factors, which may include education, training, experience, location, business needs, or market demands. The expected salary range for this role is based on the location where the work will be performed and is aligned to one of 3 compensation zones. This role is also eligible to participate in a Robinhood bonus plan and Robinhood’s equity plan. For other locations not listed,