Social Scientist Durham, NC)

• Design rigorous experiments for Hive products, including holdouts, back-tests, and A/B, geo and incrementality tests with customers and partners.
• Build repeatable experimentation frameworks, so each new product or partner can be tested quickly and consistently.
• Maintain and extend Hive's validation standards, covering out-of-sample performance, calibration, stability and uncertainty.
• Work with Hive's scientists to keep results scientifically meaningful as well as statistically significant.
• Help set the scientific bar for when a product is ready to ship.

• Analyze campaign performance data such as impressions, reach, frequency, CTR, conversions, CPA and ROAS.
• Design tests that account for how ad platforms actually work: auction dynamics, delivery optimization, pacing, audience overlap, and non-random delivery that can confound naive comparisons.
• Work with large, messy real-world datasets, and know which questions the data can and can't answer.

• Design experiments that answer the questions customers, partners and procurement teams actually ask.
• Turn results into case studies, benchmarks and proof points for commercial teams.
• Make pragmatic tradeoffs among rigor, cost, speed and what's feasible in live campaigns.
• Work with Product to prioritize the experimental work that most strengthens Hive's differentiation.
• Communicate assumptions, uncertainty and limitations clearly to technical and non-technical audiences.

• Use Claude Code and other AI tools daily to accelerate coding, analysis, diagnostics and documentation.
• Independently validate AI-generated code, assumptions and interpretations, and help set team standards for reproducible AI-assisted science.

• Exceptional experimental design skills. You've designed and run many experiments, in the field and in live commercial settings, and know how to get clean answers from messy real-world conditions.
• Deep expertise in causal inference, including randomized experiments, quasi-experimental methods and incrementality measurement.
• Hands-on experience with advertising and campaign data: impressions, CTR, conversions, CPA, ROAS, attribution and lift measurement.
• A working understanding of how ad platforms and delivery algorithms behave (auctions, optimization, pacing, targeting) and how they bias experimental results.
• Commercial experience in ad tech, marketing measurement, media, consumer intelligence, market research or consumer-facing products.
• Strong experience validating predictive or modeled data: calibration, generalization, uncertainty and bias.
• Advanced quantitative training (PhD or equivalent experience) in a field such as social or quantitative psychology, computational social science, statistics, economics, quantitative marketing or a related discipline.
• An instinct for the difference between a model that predicts well and one whose outputs mean what they claim to.
• Experience with geographic and multilevel data is a plus.
• Strong coding in Python and/or R, with comfort working directly with large datasets.
• Fluency with Claude Code, including an understanding of AI failure modes and how to verify output.
• The ability to explain complex methods simply and persuasively to commercial audiences.

We care more about experimental rigor, commercial judgment and creativity than about a specific discipline. Strong candidates might come from marketing science, ad measurement, experimentation teams at ad platforms or tech companies, media agencies, behavioral science, quantitative social science, or economics/econometrics.

• Location:
  
  Hybrid, 3 days a week in our Durham office. You must live within commuting distance.
• Employment type:
  
  Full-time.
• Work authorization:
  You must have an existing right to work in the US. We're not able to offer visa sponsorship for this role.