Data Science Intern
Mercor · San Francisco
About this 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 our platform are paid over **$4M/day** to train frontier AI models. - Our **APEX benchmark** family measures AI’s real-world impact on professional work. - Mercor Enterprise brings this infrastructure to Fortune 500 companies—capturing how their best people actually work and translating that expertise back into agents. We’re a profitable **Series C** company valued at **$10B**. We work **in-person five days a week** in **San Francisco, NYC, or London**. --- ## About the Role — Data Science Intern As a **Data Science Intern**, you’ll join a fast-moving, metrics-driven engineering team that powers critical decisions across the company. You’ll: - Analyze data that impacts **ranking, hiring efficiency, candidate experience, and revenue** - Work with **real datasets** from day one and ship insights used by **product and engineering** - Prototype models that improve how we **match talent to AI companies** - Collaborate with engineers, PMs, and leadership to design experiments, evaluate **LLM-powered systems**, and build foundations for **data integrity and visibility** You’ll move quickly while maintaining a high bar for **analytical rigor, clarity, and statistical correctness**. ### Team match areas At the end of the process, you’ll be team-matched to where you can have the most impact: 1. **Talent platform analytics** - Improve **match quality, ranking, time-to-hire, and marketplace efficiency** through experimentation and modeling. 2. **Applied AI / human data insights** - Partner 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 may work 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 to enable self-serve insights - Instrumenting events with engineers and improving **data quality, observability, and latency** - Prototyping models (e.g., **baselines to gradient boosting**) to improve matching and scoring - Evaluating **LLM-powered agents** via 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** (plus) - Excited to work **in person** in a fast-paced environment ### Nice-to-haves - **dbt** - Dashboarding tools - Recommendation/search metrics - LLM/agent evaluation experience --- ## Why Mercor - **Impact:** Your work powers how AI labs train and deploy their models - **Learning:** Early exposure to frontier AI research and engineering - **Growth:** High-velocity team where interns ship to production --- ## Benefits - Bi-annual performanc
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