Data Science Intern

Mercor

Mercor

Data Science
San Francisco, CA, USA
Posted on Nov 27, 2025

Location

San Francisco

Employment Type

Full time

Location Type

On-site

Department

EngineeringInternships

Compensation

  • $40.00 – $50.00 per hour

About Mercor

Mercor is at the intersection of labor markets and AI research. We partner with leading AI labs and enterprises to provide the human intelligence essential to AI development.

Our vast talent network trains frontier AI models in the same way teachers teach students: by sharing knowledge, experience, and context that can't be captured in code alone. Today, more than 30,000 experts in our network collectively earn over $1.5 million a day.

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 new San Francisco headquarters.

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 2025–2027).

  • 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

  • Competitive internship stipend.

  • Mentorship from experienced engineers.

  • Work on real, high-impact projects.

  • $1K monthly stipend for meals

  • Free Equinox membership

  • Team events and offsites.

  • Potential full-time return offer.