Staff Data Scientist, ML (Credit Risk)

Robinhood

Hybrid

Quick summary

Work type: Hybrid
Location: Menlo Park, CANew York, NYWashington, DC
Salary: $217,000–$255,000 / yr
Posted: 2 days ago
Nearby: 99+ roles within 25 mi

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $194k

This role $236k

$151k most similar roles pay here $266k

This role pays more than 80% of similar roles. Most pay $162,000–$225,000 — the shaded band above. At the midpoint, this role pays about $236k versus about $194k for comparable roles.

Based on 240 similar postings.

Employer

About Robinhood

Robinhood is a financial technology company offering commission-free stock, ETF, options, and cryptocurrency trading through its mobile app, aimed at democratizing access to financial markets. Industry: Financial Technology & Investment App

Robinhood currently has 83 open roles on FindRole.

Listed pay typically runs $187,000–$220,000 across 82 roles with salary data.

Most-posted roles

View all roles at Robinhood

At a glance

TL;DR · Staff Data Scientist, ML (Credit Risk)

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As a Staff Data Scientist at Robinhood, you will join the Credit Card business team in Menlo Park, CA, New York, NY, or Washington, DC to build cutting-edge credit risk models that drive customer acquisition and management decisions. You’ll collaborate with analysts and product managers to develop predictive models using both traditional and non-traditional data sources, creating innovative features and deploying them into production. Key responsibilities include model development from data preparation through deployment, as well as communicating results to senior stakeholders. Proficiency in SQL and Python is essential, along with experience in credit modeling and experimental design. This role leverages advanced analytical tools to reshape the financial services industry by making credit more accessible to everyone.

Skills

Python SQL Credit Risk Modeling Data Analysis Machine Learning Feature Engineering Model Deployment MLOps Communication Skills Experiment Design Cloud Services CI/CD

What you'll do

Build credit risk models for customer acquisitions and management.
Create datasets using traditional and non-traditional data sources.
Develop predictive risk models throughout the full lifecycle.
Deploy, maintain, and monitor models in production environments.
Communicate key results and findings to senior stakeholders.

What we're looking for

7+ years of experience in data science and credit modeling
Strong proficiency in SQL and Python for data analysis and model building
Experience designing experiments and interpreting results to guide product decisions
Domain expertise in traditional credit data, with non-traditional data experience preferred
Ability to communicate clearly with both technical and non-technical partners

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