Staff Data Scientist, Robinhood
ML, People Analytics & Insights
$191-255k
Plus bonus programs and equity ownership. Salary dependent on location
3+ days a week in office
Commission-free stock trading & investing app
Be an early applicant
Commission-free stock trading & investing app
1001+ employees
Be an early applicant
$191-255k
Plus bonus programs and equity ownership. Salary dependent on location
3+ days a week in office
1001+ employees
Company mission
To democratize finance for all.
Role
Who you are
- 7+ years of data science experience, with advanced skills in Python, SQL, and direct experience with modern data infrastructure like Snowflake, BigQuery, or dbt
- Strong product focus and experience defining user requirements, collaborating with engineers, and taking internal data tools from conception to launch
- Deep understanding of statistics, experimental design, and psychometrics or survey methodology to design research-backed questions
- Direct experience integrating language models into data pipelines to automate text processing and summarization at scale
What the job involves
- We are building an elite team, applying frontier technologies to the world’s biggest financial problems
- We’re looking for bold thinkers. Sharp problem-solvers. Builders who are wired to make an impact
- Robinhood isn’t a place for complacency, it’s where ambitious people do the best work of their careers. We’re a high-performing, fast-moving team with ethics at the center of everything we do. Expectations are high, and so are the rewards
- The Talent Management & Analytics team is scaling to its next major milestone—integrating advanced predictive insights and tactical AI into our workforce systems
- Our mission is to build the data solutions that help the entire company recruit exceptional talent, design high-performing team structures, and put active organizational insights directly into the hands of everyone making team decisions
- Operating at the intersection of data science, product development, and organizational psychology, we are transforming how Robinhood uses data to empower our workforce and anticipate organizational needs
- As a Staff Data Scientist, you will serve as the team's technical and strategic anchor, owning the vision, design, and delivery of the high-impact data products that our executives, people partners, and line managers rely on every day
- Your focus will be entirely on solving meaningful organizational problems: understanding what enables exceptional talent to thrive, accelerating team performance, and designing proactive strategies that support long-term retention across Robinhood
- This is a unique opportunity to apply state-of-the-art language models and predictive analytics to solve critical talent problems!
- Spearhead the next phase of talent intelligence: Take the team beyond descriptive reporting and build the predictive frameworks that show not just what is happening in our workforce, but what will happen next
- Architect a unified workforce data model: Pipeline data across disparate recruiting systems, performance cycles, surveys, and internal tools into a single, cohesive data model that maps the entire employee lifecycle; use AI-native workflows aggressively to parse unstructured text like exit notes and survey feedback at scale
- Define the metrics dictionary and semantic layer: Standardize how metrics like headcount, attrition, and workforce trends are measured across the company; build the semantic layers that keep this data consistent and trustworthy at scale
- Drive data access control and governance: Build the frameworks for role-based access controls and data masking so HR, Finance, and line managers have exactly the access they need without risking sensitive personnel data
- Redesign employee sentiment architecture: Replace traditional annual survey cycles with a continuous, always-on listening framework that captures real-time organizational health and highlights leading risk indicators
- Own product delivery: Act as the technical product owner for internal data interfaces—collaborating directly with Enterprise Engineering to ensure exceptional user utility, predictive accuracy, and data reliability
- Enforce rigorous statistical standards: Apply experimental design, A/B testing, and psychometric methodologies to ensure our predictive workforce models and survey frameworks are scientifically backed and statistically valid
Our take
For years, traditional brokers ruled the share trading realm, charging hefty fees that locked out everyday investors. Robinhood emerged as a disruptor, offering commission-free trading and opening the door to a new generation. Since then, expectations have continued to evolve, with investors looking not just to lower costs, but for simpler tools, clearer information, and guidance that makes the market easier to understand.
Robinhood was built to meet those changing expectations, designed from the start as a mobile-first platform that makes investor more accessible and less intimidating for people at every stage of their financial journey. Through its app, users can trade stocks and other financial instruments while benefiting from a clean interface and built-in educational support, helping them move from curiosity to confidence without unnecessary complexity.
Recently, Robinhood has strenghtned its impact too, particularly in the UK. With the launch of AI-powered Digests within its Robinhood Cortex assistant that helps users understand what's driving stock movements in plain English, while upcoming options trading and expanded educational resources add flexibility and depth. Together, these steps position Robinhood as a platform evolving alongside its users, blending technology and education to stay ahead in an ever-changing investment landscape.
Kirsty
Company Specialist at Welcome to the Jungle
Insights
Company
Funding (last 2 of 13 rounds)
Feb 2021
$2.4bn
CONVERTIBLE
Jan 2021
$1bn
LATE VC
Total funding: $5.6bn
Company HQ
Downtown Menlo Park, Menlo Park, CA
Leadership
Vlad Tenev
(Co-Founder, CEO & Chairman)Studied Mathematics at Stanford University, where they met Baiju. Dropped out of a PhD to start Robinhood. Alongside Robinhood, Vlad is also the co-founder and Executive Chairman of Harmonic.
Baiju B.
(Co-Founder)Studied Mathematics and Physics at Stanford University, where they met their Vlad and co-founded Robinhood in 2012. Baiju is also the Founder and CEO of Aetherflux.
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