Senior Data Scientist, Ads Integrity

Reddit is seeking 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.
• Design and develop scalable ads fraud detection and enforcement pipelines.
• 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 that improve fraud detection.
• Balance fraud loss, platform and advertiser risk, customer experience, false-positive costs, operational capacity, and business goals when recommending detection thresholds and enforcement strategies.
• Partner across Ads and Safety to shape strategy and roadmaps.
• Translate complex analyses into clear narratives and actionable recommendations for technical and non-technical stakeholders.

Qualifications

• Relevant experience in Data Science, Applied Science, or a related quantitative role.
• Ph.D. or M.S. degree in Statistics, Economics, Computer Science, Applied Mathematics, or another quantitative field.
• 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.
• Strong technical leadership and communication skills.

Benefits

• Comprehensive Healthcare Benefits and Income Replacement Programs
• 401k with Employer Match
• Global Benefit programs
• Family Planning Support
• Gender-Affirming Care
• Mental Health & Coaching Benefits
• Flexible Vacation & Paid Volunteer Time Off
• Generous Paid Parental Leave