Data Science Intern

About the role

ABOUT MERCOR

Mercor's mission is to organize human intelligence to power the AI economy. We're a leading AI data company, building the layer between human expertise and frontier models. Millions of domain experts on the platform are paid over $4 million per day to train frontier AI models. Mercor's APEX benchmark family measures AI's real-world impact on professional work. Mercor Enterprise brings this same infrastructure to Fortune 500 companies: helping companies capture how their best people actually work, translating that expertise directly back into agents.

Mercor is creating a new category of work where expertise powers AI advancement. Achieving this requires an ambitious, fast-paced and deeply committed team. You’ll work alongside researchers, operators, and AI companies at the forefront of shaping the systems that are redefining society. Mercor is a profitable Series C company valued at $10 billion. We work in-person five days a week in our San Francisco, NYC, or London offices.

About the Role

As a Data Science Intern at Mercor, you’ll join a fast-moving, metrics-driven engineering team whose work shapes decisions across the company. You’ll analyze data that directly affects ranking, hiring efficiency, candidate experience and revenue, work with production datasets from your first week, and ship insights that product and engineering act on.

You’ll start on the analyses and tooling your team has wanted but hasn’t had the hands for, and as needs come up you’ll take deep ownership of them, with a named mentor alongside you. You’ll move quickly while keeping a high bar for analytical rigor, clarity and statistical correctness.

Where You’ll Work

Interns start on a rolling basis, so summer, spring and fall terms all work. About three weeks before your start we’ll match you to one of two teams:

- Product Data Science. The data science function for the marketplace and talent platform: metrics for matching, ranking and hiring efficiency, event instrumentation and data integrity, experiments on the candidate and customer experience, and scoring models that change who gets surfaced for which role.

- Applied AI Data Science. The data science function inside the org that delivers human data and evaluations to frontier AI labs: operational analytics for live customer projects, automated quality control that gates what ships, and evaluation science that shows a lab where its model breaks and why.

What You’ll Work On

- Defining north-star metrics and feature-level KPIs for ranking, interview analytics and payouts

- Designing A/B tests and quasi-experiments and turning results into product decisions within days

- Building dashboards and lightweight data models so teams can self-serve insights

- Instrumenting events with engineers and improving data quality, observability and latency

- Prototyping models, from baselines to gradient boosting, to improve matching and scoring