At a glance
- Employment
- Full-time
- Workplace
- Onsite
- Location
- San Francisco
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 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
- Mercor is hiring a Pricing and Monetization Manager to own pricing structures across various data types produced for AI labs and enterprise customers.
- The role involves building pricing models, rate cards, and margin frameworks to ensure consistency and defensibility.
Responsibilities
- 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
- 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
Requirements
- 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
- 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
Preferred qualifications
- 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)
- $1.5K monthly stipend for meals
- Free Equinox membership
- $200 monthly laundry reimbursement
- $200 monthly personal wellness reimbursement
- Health, Dental, Vision insurance
Skills
- Excel
- SQL
- Pricing Strategy
- Monetization
- Revenue Operations
- Quantitative Modeling
- Cost Modeling
- Unit Economics
