Senior Data Scientist, Ads Integrity

About the role

About Our Client

The organization operates a large online community platform that hosts more than 100,000 active communities and serves approximately 130 million daily active unique visitors. The platform enables open and authentic conversations across a wide range of topics through user submissions, voting, and comments. With extensive user-generated content, the organization places strong emphasis on maintaining a safe, trustworthy, and high-quality environment for users and advertisers.

About the Opportunity

The Senior Data Scientist, Ads Integrity leads data science initiatives focused on detecting and preventing advertising fraud within the organization’s Trust & Safety function. This role is responsible for identifying emerging fraud patterns, developing scalable detection and enforcement systems, and shaping strategies that balance platform safety, advertiser protection, and operational effectiveness. The position offers significant ownership in advancing the ads integrity program and protecting the platform’s long-term growth.

Responsibilities

• Lead measurement and detection strategies for ads fraud, including developing fraud taxonomies, metrics, and evaluation frameworks.
• Analyze complex and large-scale datasets to identify emerging fraud patterns, behavioral signals, and root causes.
• Design, develop, and improve scalable fraud detection and enforcement pipelines.
• Manage the full lifecycle of fraud detection systems, including evaluation, monitoring, incident response, and continuous improvement.
• Build, maintain, and evaluate statistical, machine learning, and AI-enabled models for fraud detection.
• Develop analytical frameworks to assess model performance, enforcement effectiveness, and potential risks.
• Balance user, advertiser, business, and operational risks when recommending fraud enforcement strategies.
• Collaborate with Product, Engineering, Trust & Safety, and other cross-functional teams to align detection strategies and ensure effective implementation.
• Analyze behavioral networks and large-scale activity patterns to uncover coordinated or sophisticated fraud.
• Communicate technical findings, recommendations, and program outcomes clearly to technical and non-technical stakeholders.
• Mentor data scientists and contribute to data science best practices across the organization.

Requirements

• Professional experience in Data Science, Applied Science, or a related quantitative discipline, preferably involving advertising fraud, platform integrity, risk, or Trust & Safety.
• Ph.D. or M.S. degree in a quantitative field with relevant industry experience.
• Proven experience designing and deploying production-grade detection, risk, or enforcement systems.
• Strong understanding of fraud detection methodologies, statistical modeling, and evaluation techniques.
• Experience partnering closely with Product and Engineering teams to develop and deploy scalable solutions.
• Familiarity with artificial intelligence and large language models applied to data science or analytical workflows.
• Understanding of behavioral networks, graph-based analysis, and large-scale activity patterns.
• Strong proficiency in statistical analysis and programming using Python or a similar language.
• Advanced SQL skills and experience working with large datasets.
• Ability to investigate ambiguous problems, identify meaningful signals, and develop scalable solutions.
• Strong leadership, communication, collaboration, and stakeholder management skills.
• Ability to operate independently and take ownership of complex, high-impact initiatives.

Pay Range and Compensation Package

• The pay range and compensation package for this role will be determined based on the candidate’s experience, skills, qualifications, location, and other relevant factors.

Equal Opportunity Statement: Our client is an equal opportunity employer. They celebrate diversity and are committed to creating an inclusive environment for all employees. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, or national origin.

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