Data Scientist, Marketplace Incentives

Job Summary

This role exists to hillclimb the dataset objective: the ideal dataset, the objective function, the taxonomy, and the value of incremental data. You take that objective and maximize it: incentives, marketplace design, and collection behavior so the next hour we collect actually moves the score.

Key Responsibilities

• Treat the Dataset & Quality objective / value function as the thing you optimize - not raw hours, not vanity volume
• Design marketplace mechanics (task mix, targeting, bonuses, payouts, eligibility) so collectors produce high-value data
• Run experiments: treatment assignment, holdouts, pay and bonus tests; keep the ones that hillclimb the objective and kill the rest
• Measure whether incremental collection is improving the dataset under the value function, and report that in language ops can act on
• Work with software to ship incentive and payout changes into the collection product (not a spreadsheet that never lands)
• Watch for Goodhart: collectors optimizing the proxy instead of the objective, and close those holes

You May Be a Good Fit If You Have (Must-have Qualifications)

• Quantitative: you can take someone else’s objective function and optimize against it
• Comfortable designing and reading experiments (assignment, holdouts, power, leakage)
• Comfortable with messy field / collection data
• You like iteration: small changes, measured against the objective, shipped again

Strong Candidates May Also Have Experience with

• Experience with marketplaces, incentives, pricing, or growth experimentation (gig, two-sided, or similar)
• Experience with payouts, bonuses, or pay systems that moved real money
• You have shipped experiment results into a product, not only a notebook

Benefits

• Competitive pay
• Medical, dental, and vision packages with generous premium coverage
• $500 per month credit for waiving medical benefits
• Housing subsidy of $2k per month for those living within walking distance of the office
• Relocation support for those moving to San Francisco (Financial District) or Shenzhen (Nanshan)
• Various wellness benefits covering fitness, mental health, and more
• Daily lunch and dinner in our office
• Unlimited compute budget subject to ROI justification
• Unlimited Codex and Claude credits
• Travel

How We're Different

Build believes in the Bitter Lesson By taking a general approach of learning from humans, our addressable market is all physical labor.

We are a fully in-person team in San Francisco (Financial District) and Shenzhen (Nanshan), and greatly value engineering skills. We do not have boundaries between engineering and research, and we expect all of our technical staff to contribute to both and work across disciplines as needed.