Consumer data science plays a key role in fulfilling Reddit's mission of bringing community & belonging to the world through deep understanding of how we can better connect people to the best information and communities for them - the heart of Reddit's product - from crypto to support groups, gaming to AMAs, travel tips to memes.

Reddit's experimentation landscape presents uniquely challenging problems. Our platform is a deeply interconnected network of communities, contributors, and consumers - meaning that standard A/B testing assumptions often break down. We need a senior technical leader who thrives on these hard problems and can raise the bar for causal inference and experimentation rigor across the entire Consumer organization.

As a Senior Staff Data Scientist on the Consumer team, you will be the go-to expert on experimentation methodology, owning the most complex and high-stakes experimentation challenges across Consumer. You will shape how Reddit learns from its experiments, ensure we draw valid causal conclusions in the presence of network effects and interference, and influence product strategy through rigorous experimental design and analysis.

Responsibilities:

• Serve as the technical authority on experimentation methodology across Consumer, setting standards for design, analysis, and interpretation of experiments in a complex, networked environment
• Tackle the hardest experimentation problems at Reddit, including spillover and network effects, interference between treatment and control, two-sided experimentation, and long-run effect estimation
• Develop and advance methods for causal inference in settings where standard randomization assumptions are violated, such as cluster-randomized designs, switchback experiments, and synthetic control approaches
• Design experimentation frameworks and guardrail metrics that account for ecosystem-level effects, ensuring product teams can measure true causal impact rather than biased local estimates
• Identify opportunities where improved experimentation methodology can unlock product insights that were previously unmeasurable or ambiguous
• Build and scale self-serve experimentation tools, platforms, and best-practice documentation that increase experimentation velocity and literacy across product, engineering, and design teams
• Influence the long-term product strategy by driving learning through well-designed experiments and translating experimental results into clear, actionable recommendations for senior leadership
• Mentor and elevate other data scientists across the organization on experimentation best practices, causal reasoning, and statistical rigor
• Publish and share methodological advances internally and, where appropriate, externally to contribute to the broader experimentation and causal inference community

Required Qualifications:

• Ph.D. in Statistics, Econometrics, Economics, Computer Science, or a related quantitative field with a strong focus on causal inference or experimentation methodology; or M.S. with equivalent depth of expertise
• For M.S. holders: 12+ years of industry experience in applied science, data science, or experimentation-focused roles
• For Ph.D. holders: 8+ years of industry experience in applied science, data science, or experimentation-focused roles
• Deep expertise in causal inference, including practical experience with challenges such as network interference / spillovers, two-sided experimentation, switchback designs, cluster randomization, and/or synthetic control methods
• Strong theoretical grounding in experimental design, including power analysis, variance reduction techniques, sequential testing, and multiple comparison corrections
• Experience with experimentation platforms at scale (e.g., building or significantly extending an internal experimentation platform)
• Expert knowledge of SQL and proficiency in R and/or Python for statistical computing
• Track record of designing and analyzing experiments at scale in complex or networked environments
• Demonstrated ability to influence product and organizational strategy through experimentation insights
• Demonstrated ability to take ambiguous, technically complex problems and solve them in a structured, hypothesis-driven way
• Excellent communication skills with the ability to explain nuanced statistical concepts and tradeoffs to both technical and non-technical senior stakeholders
• Experience mentoring data scientists and building organizational capability in experimentation and causal reasoning
• Comfortable in innovative and fast-paced environments with a bias toward action

Preferred Qualifications:

• Published research or industry contributions in areas such as interference in experiments, network experimentation, or marketplace causal inference
• Familiarity with Bayesian experimental methods, bandit algorithms, or adaptive experimental designs
• Experience with social network or user-generated content platforms where community-level dynamics create non-trivial experimentation challenges

Benefits:

• Comprehensive Healthcare Benefits and Income Replacement Programs
• 401k with Employer Match
• Global Benefit programs that fit your lifestyle, from workspace to professional development to caregiving support
• Family Planning Support
• Gender-Affirming Care
• Mental Health & Coaching Benefits
• Flexible Vacation & Paid Volunteer Time Off
• Generous Paid Parental Leave

#LI-REMOTE

Pay Transparency:

This job posting may span more than one career level.

In addition to base salary, this job is eligible to receive equity in the form of restricted stock units, and depending on the position offered, it may also be eligible to receive a commission. Additionally, Reddit offers a wide range of benefits to U.S.-based employees, including medical, dental, and vision insurance, 401(k) program with employer match, generous time off for vacation, and parental leave. To learn more, please visit https://www.redditinc.com/careers/.

To provide greater transparency to candidates, we share base salary ranges for all US-based job postings regardless of state. We set standard base pay ranges for all roles based on function, level, and country location, benchmarked against similar stage growth companies. Final offer amounts are determined by multiple factors including, skills, depth of work experience and relevant licenses/credentials, and may vary from the amounts listed below.

The base salary range for this position is:

$232,500-$325,500 USD

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