Senior Data Scientist (Ads Integrity)

Location: Remote within the United States; optional access to offices in San Francisco, Los Angeles, New York City, and Chicago.

Base salary: $190,800–$267,100 USD per year, plus potential equity and, depending on the position, commission.

Company

A large online community platform built around user-generated communities, conversations, and trust and safety.

What you will do

• Lead the measurement and detection strategy for ads fraud, including taxonomies, labels, sampling plans, metrics, and evaluation frameworks.
• Analyze large datasets and behavioral networks to identify emerging fraud patterns, root causes, and business impact.
• Design scalable detection and enforcement pipelines with feature generation, rules, models, near-real-time scoring, actioning, review feedback loops, and observability.
• Own the detection lifecycle from backtesting and threshold calibration through launch validation, monitoring, drift detection, incident response, rollback, and retirement.
• Build statistical, machine learning, and GenAI-enabled models or prototypes for fraud detection, risk identification, investigator efficiency, and enforcement quality.
• Partner with Ads, Safety, Engineering, Machine Learning, Operations, Policy, and Legal to shape roadmaps, strengthen data foundations, and mentor data scientists and analysts.

Requirements

• Relevant experience in data science, applied science, or a quantitative discipline, preferably in ads or financial fraud, account risk, Trust & Safety, platform integrity, or enforcement engineering.
• Ph.D. or M.S. in statistics, economics, computer science, applied mathematics, or another quantitative field; 4+ years of industry data science experience with an M.S. or 2+ years with a Ph.D.
• Experience building or materially shaping production detection and automated enforcement pipelines using batch or streaming data, feature engineering, rules or models, decisioning, monitoring, and feedback loops.
• Strong knowledge of fraud and abuse detection evaluation, including precision and recall, calibration, threshold selection, false-positive analysis, drift detection, and adversarial adaptation.
• Experience applying AI and large language models to practical data science workflows, plus knowledge of behavioral networks, graph analysis, clustering, anomaly detection, or natural language processing.
• Fluency in statistical analysis, Python or a similar programming language, and SQL, with strong technical leadership and communication skills.

Culture & Benefits

• Fully remote work within the United States, with optional office access for employees near listed locations.
• Comprehensive healthcare and income replacement programs.
• 401(k) with employer match and global benefit programs supporting workspace, professional development, and caregiving.
• Family planning support, gender-affirming care, and mental health and coaching benefits.
• Flexible vacation, paid volunteer time off, and generous paid parental leave.

Hiring process

• In select roles and locations, interviews may be recorded, transcribed, and summarized by AI; candidates can opt out before scheduled interviews.