The opportunity
Our mission is to democratize finance for all. An estimated $124 trillion of assets will be inherited by younger generations in the next two decades.
What you'll do
Own Robinhood’s NPS program end to end: survey design, sampling and weighting methodology, fielding cadence, data quality, key driver analysis, and executive reporting
Own the broader survey and research portfolio, including safety perception: research, brand and product sentiment studies, benchmarking and trend tracking, and ad hoc voice-of-customer work
Analyze open-text and responses at scale, including with LLM-assisted: classification, while keeping methodology defensible
Partner with Product, Research, Operations, Marketing, and Brokerage: leadership to close the loop from survey signal to product and policy change
Make agentic workflows the default operating model for the team. Design how: analysis, pipeline development, QA, documentation, and recurring reporting get delegated to agents, and hold the team accountable to that standard
Build durable agent infrastructure rather than one-off prompts: reusable skills, context files, MCP tool integrations, evaluation harnesses, and guardrails that make agent output trustworthy enough for finance-grade and research-grade decisions
What they're looking for
- Lead both sides of the analytics stack: rigorous data science (measurement, experimentation, modeling) and the analytics engineering foundation (pipelines, tooling, data models) that agents and humans build on
- Lead, mentor, and develop a team of data scientists and engineers; operate as: a player-coach who stays hands-on in the terminal and in the code and ships real work alongside the team
- Foster a culture of technical excellence, strong business judgment,: methodological rigor, and clear accountability
- Partner closely with Finance, Product, Engineering, Operations, and other key: departments to translate complex business questions into scalable, trustworthy analytics
