Senior Data Scientist, Ads Integrity

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Senior Data Scientist, Ads Integrity based in the United States.

This is a high-impact senior data science role focused on protecting a large-scale digital platform and its advertising ecosystem from fraud and abuse.

You’ll lead the strategy for detecting sophisticated ads fraud, from defining measurement frameworks to developing scalable enforcement solutions.

The role combines advanced analytics, machine learning, behavioral analysis, and experimentation to uncover emerging threats and reduce financial and platform risk.

You’ll work closely with Product, Engineering, Machine Learning, Operations, Policy, Legal, and Safety teams to turn investigations into durable systems.

As an early leader in a developing area, you’ll have substantial ownership in shaping strategy, roadmaps, processes, and foundational capabilities.

You’ll operate in an environment that values rigorous analysis, pragmatic decision-making, technical leadership, and continuous innovation.

Your work will directly influence advertiser trust, user safety, platform integrity, and the long-term health of the advertising business.

Accountabilities

• Lead the measurement and detection strategy for ads fraud by defining fraud taxonomies, labels, sampling methodologies, metrics, and rigorous evaluation frameworks.
• Analyze large-scale datasets and behavioral networks to identify emerging fraud patterns, quantify their impact, uncover root causes, and translate insights into actionable detection and enforcement requirements.
• Partner with Engineering and Machine Learning teams to design and develop scalable fraud detection and automated enforcement pipelines, including feature generation, rules, models, scoring, actioning, feedback loops, and observability.
• Own the complete detection lifecycle, including backtesting, threshold calibration, offline and online evaluation, experimentation, launch validation, monitoring, drift detection, incident response, rollback, and retirement.
• Develop and evaluate statistical, machine learning, and GenAI-enabled models or prototypes that improve fraud detection, risk identification, investigation efficiency, and enforcement quality.
• Balance fraud losses, advertiser and platform risk, customer experience, false-positive costs, operational capacity, and business objectives when recommending detection thresholds and enforcement strategies.
• Collaborate across Ads and Safety functions to shape strategic priorities, roadmaps, data foundations, policies, and enforcement capabilities while ensuring governance and compliance requirements are met.
• Translate complex analytical findings into clear narratives, insights, and recommendations for both technical and non-technical audiences, including senior leadership.
• Mentor data scientists and analysts while contributing technical leadership to a growing ads integrity function.

Requirements

• Master’s degree in Statistics, Economics, Computer Science, Applied Mathematics, or another quantitative discipline with 4+ years of industry data science experience, or a Ph.D. in a relevant quantitative field with 2+ years of industry experience.
• Relevant experience in Data Science, Applied Science, or a related quantitative discipline, ideally within ads fraud, financial fraud, account risk, Trust & Safety, platform integrity, or enforcement engineering.
• Demonstrated experience building or significantly shaping production detection and automated enforcement systems, including batch or streaming data, feature engineering, rules or models, decisioning, monitoring, and feedback loops.
• Strong knowledge of fraud and abuse detection methodologies, including label design, precision and recall tradeoffs, calibration, threshold selection, false-positive analysis, drift detection, and adversarial adaptation.
• Proven ability to partner with Product and Engineering teams to turn analytical insights and prototypes into reliable, scalable production systems.
• Experience applying AI and large language models to practical data science use cases such as threat discovery, classification, signal development, investigation automation, or detection and enforcement.
• Strong understanding of behavioral networks and large-scale activity patterns, with experience in graph or network analysis, clustering, anomaly detection, or natural language processing considered valuable.
• Advanced proficiency in statistical analysis, Python or a comparable programming language, and SQL, with the ability to independently navigate complex data systems and unfamiliar codebases.
• Strong analytical and problem-solving abilities, with a track record of breaking ambiguous problems into precise, actionable components and developing scalable solutions.
• Excellent technical leadership, communication, and stakeholder management skills, including the ability to influence cross-functional roadmaps and communicate complex concepts clearly to senior and non-technical audiences.
• Comfortable operating with significant autonomy in a rapidly evolving environment and taking ownership of high-impact initiatives.

Benefits

• Base salary range of $190,800-$267,100 USD, depending on factors such as skills, experience, credentials, and location.
• Eligibility for equity in the form of restricted stock units.
• Comprehensive healthcare benefits and income replacement programs.
• 401(k) program with employer match.
• Global benefits designed to support workspace needs, professional development, caregiving, and different lifestyles.
• Family planning support.
• Gender-affirming care.
• Mental health and coaching benefits.
• Flexible vacation and paid volunteer time off.
• Generous paid parental leave.
• Fully remote-friendly work within the United States.
• Opportunities to make a significant impact in a growing Trust & Safety and ads integrity organization.
• Supportive environment focused on technical growth, collaboration, and professional development.