Senior Data Scientist, Ads Integrity
Remote - United States · Senior · Contract
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About the role
- 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.
Responsibilities
- Lead the measurement and detection strategy for ads fraud by defining fraud taxonomies, labels, sampling plans, metrics, and evaluation frameworks that make performance measurable and defensible.
- Partner across Ads and Safety to shape strategy and roadmaps, strengthen data foundations, close policy and enforcement gaps, and ensure solutions meet governance and compliance standards.
- as an early leader in a greenfield space, you will help define the strategy, shape cross-functional roadmaps, build foundational capabilities, and expand your scope as Reddit's ads integrity program matures.
- Family Planning Support
Requirements
- Relevant experience in Data Science, Applied Science, or a related quantitative role, preferably in ads fraud, financial fraud, or account risk, Trust & Safety, platform integrity, or enforcement engineering.
- Ph.D. or M.S. degree in Statistics, Economics, Computer Science, Applied Mathematics, or another quantitative field
- with an M.S., 4+ years of industry data science experience, or with a Ph.D., 2+ years of industry data science experience.
- experience with methods such as graph or network analysis, clustering, anomaly detection, or natural language processing is valuable.
- Fluency in statistical analysis, Python or a similar programming language, and SQL, with the ability to work independently across complex data systems and unfamiliar codebases.
- Ability to tackle ambiguously defined problems, deconstruct them into precise and tractable components, and move from investigation to scalable, reusable solutions.
- Strong technical leadership and communication skills, with a track record of influencing cross-functional roadmaps, aligning stakeholders, and explaining complex topics to technical and non-technical audiences.
- Demonstrated experience building or materially shaping production detection and automated enforcement pipelines, including batch or streaming data, feature engineering, rules or models, decisioning, monitoring, and feedback loops.
- Strong command of fraud or abuse detection methods and evaluation, including label design, precision and recall tradeoffs, calibration, threshold selection, false-positive analysis, drift detection, and adversarial adaptation.
- Experience applying AI and large language models (LLMs) to practical data science workflows, such as threat discovery, content classification, signal development, investigation automation, or detection and enforcement systems.
- Deep understanding of complex behavioral networks or large-scale activity patterns
Nice to have
- Experience partnering closely with Product and Engineering teams to translate analyses and prototypes into reliable production systems
- experience working across Ads, Safety, fraud, risk, or platform-integrity organizations is preferred.
Compensation
- 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.
- 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.
Benefits
- Comprehensive Healthcare Benefits and Income Replacement Programs
- Global Benefit programs that fit your lifestyle, from workspace to professional development to caregiving support
- Mental Health & Coaching Benefits
- Flexible Vacation & Paid Volunteer Time Off
- Generous Paid Parental Leave
- 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.
Company info
- Reddit is a community of communities.
- For more information, visit www.redditinc.com.
- Reddit is continuing to grow our teams with the best talent.
- This role is completely remote friendly within the United States.
- If you happen to live close to one of our physical office locations (San Francisco, Los Angeles, New York City & Chicago) our doors are open for you to come into the office as often as you'd like.
- Reddit is poised to innovate and grow like never before, and Safety is a critical accelerant of that growth.
- The Safety org is Reddit's central Trust & Safety organization, protecting users from bad experiences by stopping harmful content, behaviors, and abuse across the platform.
- We are looking for a Senior Data Scientist to lead ads fraud detection and scaled enforcement within Safety.
- You will partner closely with Ads Product, Engineering, Machine Learning, Operations, Policy, Legal, and fellow Safety data scientists to identify emerging ads fraud, define rigorous measurement and evaluation standards, and turn investigations into durable signals, models, rules, and enforcement pipelines.
Equal opportunity
- Reddit is proud to be an equal opportunity employer, and is committed to building a workforce representative of the diverse communities we serve.
- If, due to a disability, you need an accommodation during the interview process, please let your recruiter know.
Visa & Work Authorization
- You will have the opportunity to opt out of recording, transcription and summarization prior to any scheduled interviews.
This listing is sourced directly from Reddit's careers page and normalized into a canonical job model.