Sr. Staff Data Scientist

Responsibilities

• Define the long-term data science vision & strategy across ads measurement, signal quality, identity, attribution, and privacy.
• Establish how Reddit should evaluate advertiser value, measurement quality, and signal utility across first-party and third-party products.
• Create rigorous frameworks for validating lift, attribution, identity quality, modeled conversions, signal loss recovery, and privacy-aware measurement. Define ground truth, objective functions, quality metrics, guardrails, and decision frameworks.
• Lead the evolution of Reddit’s experimentation and lift methodologies across Brand Lift, Conversion Lift, Split Testing, and emerging measurement products. Improve study quality, reduce bias and contamination, and develop scalable diagnostics.
• Partner with Ads Engineering to operationalize complex causal models.
• Quantify how signal quality, match rates, identity resolution, modeled conversions, and privacy changes affect bidding efficiency, CPA, ROAS, and advertiser outcomes.
• Partner with modeling and ranking teams to translate measurement improvements into performance gains.
• Lead a privacy-first measurement paradigm.
• Lead cross-org efforts to define reusable methodologies, dashboards, scorecards, quality metrics, and best practices.
• Partner with senior leaders across Product, Engineering, Sales, Marketing Science, Legal/Privacy, and Ads leadership to shape roadmap decisions.
• Mentor Staff and Senior data scientists, sponsor high-impact technical work, and raise the bar for causal inference, measurement science, identity evaluation, data quality, and cross-functional decision-making.

Requirements

• Advanced degree in Statistics, Economics, Mathematics, Computer Science, Operations Research, Physics, or a related quantitative field, or equivalent industry experience.
• 10+ years of industry experience in data science, applied science, economics, statistics, or a related quantitative role.
• Deep expertise in ads measurement, experimentation, causal inference, attribution, marketplace measurement, or ads optimization.
• Proven track record leading ambiguous, cross-functional, multi-pillar problem spaces with measurable business impact.
• Strong command of statistical modeling, experimental design, causal inference, and measurement methodology.
• Experience defining metrics, evaluation frameworks, quality guardrails, and decision systems for complex products.
• Demonstrated ability to balance long-term strategic vision with hands-on execution of complex technical ideas.
• Advanced proficiency in SQL and Python or R.
• Ability to influence senior product, engineering, and business leaders through clear technical judgment and communication.
• Demonstrated ability to mentor senior ICs and improve technical standards across a data science organization.
• Demonstrated agility in adopting AI tools to amplify your personal output.

Nice-to-Haves

• Experience with ads identity, conversion modeling, signal loss, modeled conversions, match-rate optimization, or identity graph evaluation.
• Experience with lift measurement, brand lift, conversion lift, incrementality testing, MMM, MTA, or third-party measurement partnerships.
• Experience working on privacy-constrained measurement, clean rooms, aggregation, consent-aware systems, or privacy-preserving modeling.
• Experience partnering with ranking, bidding, or machine learning teams to connect measurement quality to optimization outcomes.
• Familiarity with two-sided marketplaces, auction systems, performance advertising, or advertiser-facing measurement products.
• Experience building durable internal frameworks, training programs, scorecards, or methodology standards adopted across an organization.