About the role
Remote - United States
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.
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.
Responsibilities
Lead the measurement and detection strategy for ads fraud by defining fraud taxonomies, labels, sampling plans, metrics, and evaluation frameworks.
Analyze large, complex datasets and networks of behavior to uncover emerging fraud patterns, size their impact, identify root causes, and translate findings into detection and enforcement requirements.
Design and develop scalable ads fraud detection and enforcement pipelines in partnership with Engineering and Machine Learning.
Own the full detection lifecycle: backtesting, threshold calibration, offline and online evaluation, launch validation, experimentation, monitoring, drift detection, incident response, rollback, and retirement.
Build and maintain statistical, machine learning, and GenAI-enabled models or prototypes.
Balance fraud loss, platform and advertiser risk, customer experience, false-positive costs, operational capacity, and business goals.
Partner across Ads and Safety to shape strategy and roadmaps.
Translate complex analyses into clear narratives and actionable recommendations, and mentor other data scientists and analysts.
Qualifications
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.
Demonstrated experience building or materially shaping production detection and automated enforcement pipelines.
Strong command of fraud or abuse detection methods and evaluation.
Experience partnering closely with Product and Engineering teams.
Experience applying AI and large language models (LLMs) to practical data science workflows.
Deep understanding of complex behavioral networks or large-scale activity patterns.
Fluency in statistical analysis, Python or a similar programming language, and SQL.
Ability to tackle ambiguously defined problems and move from investigation to scalable, reusable solutions.
Strong technical leadership and communication skills.
Benefits:
Comprehensive Healthcare Benefits and Income Replacement Programs
401k with Employer Match
Family Planning Support
Gender-Affirming Care
Mental Health & Coaching Benefits
Flexible Vacation & Paid Volunteer Time Off
Generous Paid Parental Leave
The base salary range for this position is: $190,800 - $267,100 USD
Reddit is proud to be an equal opportunity employer, and is committed to building a workforce representative of the diverse communities we serve.
Minimum requirements
- M.S. with 4+ years or Ph.D. with 2+ years in Data Science or related quantitative field, preferably in ads fraud or Trust & Safety.
- Proven experience building production detection and automated enforcement pipelines.
- Proficiency in fraud detection methods, Python/SQL, AI/LLMs, and strong collaboration with Product and Engineering teams.
This listing was parsed by AI and may not be complete. Check the official posting on Reddit's site for the most accurate information.