Senior Data Scientist, Ads Integrity

Written by the T&S Network from Reddit's posting.

Ads fraud detection and scaled enforcement inside Reddit's central Trust & Safety org, covering the ads surface. The role leads a greenfield ads integrity program, working with Ads Product, Engineering, Machine Learning, Operations, Policy and Legal to find emerging fraud and turn investigations into signals, models, rules and enforcement pipelines.

• Fraud and scams

What you'd do

• Define fraud taxonomies, labels, sampling plans, metrics and evaluation frameworks for ads fraud measurement.
• Analyze large datasets and behavior networks to find emerging fraud patterns and size their impact.
• Design and build scalable detection and enforcement pipelines with Engineering and ML, including near-real-time scoring and actioning.
• Own the detection lifecycle, from backtesting and threshold calibration through launch validation, monitoring, drift detection, rollback and retirement.
• Build statistical, ML and GenAI-enabled models or prototypes to improve fraud detection and investigator efficiency.
• Balance fraud loss, advertiser risk, false-positive costs and operational capacity when setting thresholds and enforcement strategy.
• Brief technical teams and senior leaders on findings with clear actions, and coach other data scientists and analysts.

What it asks for

• Relevant experience in data science or applied science, preferably in ads fraud, financial fraud, account risk, Trust & Safety or platform integrity.
• Ph.D. with 2+ years industry data science experience, or M.S. with 4+ years.
• Hands-on work building or improving live detection systems and automated enforcement, including the feedback loops that feed them.
• Deep working knowledge of fraud detection methods and how to judge them, including the trade between catching bad activity and wrongly flagging good activity, probability scoring accuracy, and how bad actors change tactics.
• Experience applying LLMs and AI to data science workflows such as threat discovery or investigation automation (preferred).
• Experience with graph analysis, clustering, anomaly detection or NLP (valuable).
• Fluency in statistics, Python or similar, and SQL.

Our best summary of the posting, and it can be wrong. The employer's posting is what counts: read it in full on Redditnorth_east before you apply. If we got something wrong, report this listing.