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 that powers critical decisions across the company. You’ll analyze data that directly impacts ranking, hiring efficiency, candidate experience, and revenue. From day one, you’ll work with real datasets, ship insights used by product and engineering, and prototype models that improve how we match talent to AI companies.
You’ll work closely with engineers, PMs, and leadership, designing experiments, evaluating LLM-powered systems, and building the foundations of data integrity and visibility across the platform. You’ll move quickly while maintaining a high bar for analytical rigor, clarity, and statistical correctness.
At the end of the process, you’ll be team-matched to where you can have the most impact, on one of the following:
Talent platform analytics – improving match quality, ranking, time-to-hire, and marketplace efficiency through experimentation and modeling.
Applied AI/human data insights – partnering with leading AI labs (OpenAI, Anthropic, Google) to design evaluation rubrics, run human-in-the-loop studies, and understand how experts shape post-training data for frontier models.
What You’ll Work On
As an intern, you’ll take on projects such as:
Defining north-star metrics and feature-level KPIs for ranking, interview analytics, and payouts systems.
Designing and running A/B tests and quasi-experiments; translating results into product decisions within days.
Building dashboards and lightweight data models that empower teams to 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 systems.
Evaluating LLM-powered agents through rubric design, human-in-the-loop experiments, and guardrail canary testing.
What We’re Looking For
Pursuing a degree in a quantitative field (graduating 2026–2028).
Strong fundamentals in statistics, SQL, and Python.
Experience with experiment design, causal reasoning, and data analysis.
Ability to communicate clearly with engineers, product managers, and leadership.
Curiosity about LLM evaluation, retrieval, ranking, or marketplace dynamics (a plus).
Excited to work in person and thrive in a fast-paced environment.
Nice-to-haves: experience with dbt, dashboarding tools, recommendation/search metrics, or LLM/agent evaluation.
Why Mercor
Impact: Your work powers how AI labs train and deploy their models
Learning: Get early exposure to frontier AI research and engineering
Growth: Work with a high-velocity team where interns ship to production
Benefits
Bi-annual performance bonus structure
Generous equity grant vested over 4 years
Up to $15k Relocation bonus
$10K housing bonus (if you live within 0.5 miles of our office)
$1.5K monthly stipend for meals
Free Equinox membership
$200 monthly laundry reimbursement
$200 monthly personal wellness reimbursement
Health, Dental, Vision insurance
Skills Required
- Pursuing a degree in a quantitative field, graduating between 2026 and 2028
- Strong fundamentals in statistics
- Strong SQL skills
- Strong Python skills
- Experience with experiment design
- Experience with causal reasoning and data analysis
- Ability to communicate clearly with engineers, product managers, and leadership
- Willingness to work in person five days per week in San Francisco, New York City, or London
- Curiosity about LLM evaluation, retrieval, ranking, or marketplace dynamics
- Experience with dbt
- Experience with dashboarding tools
- Experience with recommendation or search metrics
- Experience with LLM or agent evaluation
Mercor Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Mercor and has not been reviewed or approved by Mercor.
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Fair & Transparent Compensation — Pay is considered competitive across many roles, with clear hourly ranges and an hourly/pay‑per‑task mix designed to align rates with expertise. The structure emphasizes transparent, appropriate pay levels and guarantees payment for legitimate logged time.
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Strong & Reliable Incentives — Payments are processed on a predictable weekly cadence via Stripe/Wise, and some tracks offer additional weekly bonus incentives for top performers. This combination of regular payouts and performance bonuses supports dependable earnings when projects are active.
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Equity Value & Accessibility — Select full‑time roles include generous equity grants alongside cash perks such as relocation and housing bonuses. These elements increase total compensation for those positions.
Mercor Insights
What We Do
We use AI to understand human ability and match talent with the opportunities they're best suited for.
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