About Mercor

Mercor’s mission is to organize human intelligence for the AI economy. We build the infrastructure that enables frontier AI labs and enterprises to train, evaluate, and improve AI on real-world professional work. More than five million experts have joined our network, and we pay out over $5 million daily for their knowledge and expertise.

We built our training and evaluation infrastructure alongside the world’s leading AI labs. Now, we’re bringing those capabilities to enterprises across industries, enabling them to train, evaluate, and improve AI using their own expertise and standards. Our APEX benchmarks measure how AI performs on economically valuable work, while our enterprise evaluations and post-training capabilities turn those insights into measurable improvements across real-world workflows.

Our work sits at the intersection of frontier AI, human expertise, and real-world application. We’re solving problems few companies have encountered, with the opportunity to influence what the world’s most advanced AI systems become capable of doing. We’re looking for people who bring different perspectives, take ownership, exercise sound judgment, and hold themselves to an exceptionally high standard. You’ll have the opportunity to do consequential work alongside talented colleagues who challenge one another, collaborate openly, and share a commitment to excellence.

Mercor is profitable and recently raised a $750 million Series D at a $20 billion valuation. We work in person five days a week in San Francisco, New York, and London.

The Role

Mercor produces all sorts of data of data types, for AI labs and enterprise customers. We're hiring someone to own pricing structures across our data types.

This person will build the pricing models, rate cards, and margin frameworks to ensure pricing is consistent and defensible.

What You'll Do

Acquisition pricing & cost modeling (buy side)

Establish fair market value for the data we buy — by data type, domain, and end buyer — and set the acquisition cost ceilings that bound what we'll pay

Track competitor bidding behavior and maintain the cost curves that tell us when to pay up to win a corpus and when to walk

Model fully-loaded cost to serve: acquisition price, extraction, human QC, anonymization/PII, and LLM inference — not just what we pay the vendor

Define the priceable unit for each data type — per repo, per file, per video minute, per audio hour — and the quality attributes that move price within a unit

Monetization & margin strategy (sell side)

Design pricing and packaging frameworks for data by data type, volume, format, and customer segment

Build rate cards and tiered pricing for recurring, repeatable data products

Own unit economics per deal and per data product, including transfer pricing, internal chargeback, and direct vs. indirect revenue attribution across account P&Ls

Build the pricing/forecasting toolkit Finance and leadership use to evaluate new data products before launch

Continuously test and refine pricing using win/loss data, renewal behavior, and market feedback

What We're Looking For

6+ years in pricing strategy, monetization, revenue operations, or a related analytical/strategy role — ideally at a data, marketplace, or B2B SaaS company

Strong financial/quantitative modeling skills — fluent in Excel/Sheets; SQL a strong plus

Track record of building pricing models from scratch, not just tuning ones already in place

Comfortable operating with real ambiguity — public benchmarks for pricing data assets are thin, so structured judgment matters as much as data

Sharp cross-functional communicator — this person works daily with Sourcing, Sales, Finance, and Product

Nice to Have

Experience pricing a two-sided marketplace (a cost/supply side and a demand/sell side), not just a single-sided product

Background in AI training data, or market data

Benefits

Bi-annual performance bonus structure

Generous equity grant vested over 4 years

Up to $15k Relocation bonus

$10K proximity bonus (if you live within 0.5 miles of our office)