Data Science Intern

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

• Evaluating LLM-powered systems through rubric design, human-in-the-loop experiments and guardrail testing

What We’re Looking For

• Pursuing a degree in a quantitative field, graduating 2027 (potentially 2028)

• Strong fundamentals in statistics, SQL and Python

• Experience with experiment design, causal reasoning and data analysis

• Clear communication with engineers, product managers and leadership

• Curiosity about LLM evaluation, retrieval, ranking or marketplace dynamics

• Excited to work in person in San Francisco

• Nice to have: dbt, dashboarding tools, recommendation or search metrics, LLM and agent evaluation

Compensation and Benefits

• $10K housing bonus if you live within 0.5 miles of our office during your internship

• $1.5K monthly stipend for meals/rideshare

• Health, dental and vision insurance

• 401(k) eligibility