Senior Staff Data Scientist - Consumer Experimentation
- Status
- Open
- Remote policy
- Remote
- Employment type
- Not stated
- Salary
- 232,500-325,500 USD / year
- Categories
- Consumer Data Science
- Source
- First observed
- 2026-08-18 21:01 UTC
- Last seen
- 2026-10-04 15:55 UTC
- Source claims posted
- 2026-06-01 18:44 UTC
- Consecutive misses
- 0 of 3
What the posting says
Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 130 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com.
Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 126 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com.
Reddit is poised to rapidly innovate and grow like no other time in its history. This is a unique opportunity to leave your mark on one of the most influential and trafficked corners of the internet.
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
In select roles and locations, the interviews will be recorded, transcribed and summarized by artificial intelligence (AI). You will have the opportunity to opt out of recording, transcription and summarization prior to any scheduled interviews.
During the interview, we will collect the following categories of personal information: Identifiers, Professional and Employment-Related Information, Sensory Information (audio/video recording), and any other categories of personal information you choose to share with us. We will use this information to evaluate your application for employment or an independent contractor role, as applicable. We will not sell your personal information or disclose it to any third party for their marketing purposes. We will delete any recording of your interview promptly after making a hiring decision. For more information about how we will handle your personal information, including our retention of it, please refer to our Candidate Privacy Policy for Potential Employees and Contractors.
Reddit is proud to be an equal opportunity employer, and is committed to building a workforce representative of the diverse communities we serve. Reddit is committed to providing reasonable accommodations for qualified individuals with disabilities and disabled veterans in our job application procedures. If, due to a disability, you need an accommodation during the interview process, please let your recruiter know.
Quality
- + Salary range stated weight 35%
- + Remote policy stated weight 20%
- + Location stated weight 15%
- + Organisation stated weight 15%
- + Publication date stated weight 15%
Based on 97 observation(s).
- + Days open - fineOpen for 46 days so far
- + Reopen count - fineNever reopened
- + Salary range removed after publication - fineSalary range has not been removed since publication
- + Salary range narrowed - fineSalary range has not narrowed since publication
- + Missing/reappear cycles - fineNo missing-then-reappeared cycles observed
Timeline
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#1025402 2026-09-27 02:20 UTCModified
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#1032164 2026-09-27 14:20 UTCModified
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#1038880 2026-09-28 02:28 UTCModified
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#1046997 2026-09-28 14:28 UTCModified
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#1057185 2026-09-29 02:28 UTCModified
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#1068433 2026-09-29 14:36 UTCModified
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#1083359 2026-09-30 02:43 UTCModified
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#1091970 2026-09-30 14:43 UTCModified
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#1103108 2026-10-01 02:44 UTCModified
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#1114626 2026-10-01 14:49 UTCModified
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#1125952 2026-10-02 02:59 UTCModified
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2026-10-01T08:08:31-04:00->2026-10-01T20:20:53-04:00
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#1137165 2026-10-02 15:26 UTCModified
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#1148744 2026-10-03 03:48 UTCModified
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#1156602 2026-10-03 15:54 UTCModified
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2026-10-02T20:07:44-04:00->2026-10-03T08:09:18-04:00
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#1165435 2026-10-04 03:55 UTCModified
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2026-10-03T08:09:18-04:00->2026-10-03T20:08:54-04:00
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#1171636 2026-10-04 15:55 UTCModified
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2026-10-03T20:08:54-04:00->2026-10-04T08:27:27-04:00
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