Role & Responsibilities :

You'll own the product direction for ML-driven capabilities bidding algorithms, traffic quality (fraud detection), and audience modeling while maintaining the operational rigor required for MRC/TAG compliance. You'll be part of the broader PM community, following established practices and gradually expanding your scope.

Product Management :

- Own and prioritize the Data Science team backlog; define user stories and acceptance criteria.

- Lead scopes where domain knowledge is primarily algorithm/ML-driven; support cross team scopes as a secondary PM.

- Participate in roadmap planning, sprint planning, and PM syncs, and uphold established PM ways of working from templates and documentation standards to consistent communication and proactive stakeholder management.

- Bridge Product leadership and Data Scientists translate business needs into technical priorities and vice versa.

Algorithm Analysis & Validation:

- Analyze and validate ML algorithm outputs (bidding, delivery predictions, audience models) against business KPIs.

- Test model outputs, identify when and why algorithms underperform, and provide actionable feedback to data scientists.

- Conduct advanced investigation and analysis for algorithm-related performance issues.

- Support A/B test design and analysis for algorithm changes.

Ad & Traffic Quality (Fraud) Operations:

- Investigate fraud-related issues IP/domain/app unblocking, ads.txt issues, discrepancy reports, DOOH/CTV/Retail Media whitelisting.

- Manage fraud blacklists (IP, domain, UA, app) using internal tools.

- Run compliance cycles Backward Looking Assessments, quarterly risk assessments, IVT filter reviews, TAG/IWL list updates, methodology disclosures and look for opportunities to AI automate the recurring, repeatable parts rather than only running them manually.

- Support TAG/MRC audits and contribute to RFI/RFP responses on traffic quality.

Industry & AI Awareness:

- Track AdTech trends, AI/ML developments, and competitive landscape to inform priorities.

Skills Required:

- 35 years in a product, analytics, or technical role working alongside data science/ML teams.

- 12 years of experience in AdTech or programmatic advertising.

- Hands-on experience testing or analyzing ML model outputs (not building them).

- Strong analytical skills SQL, data analysis tools, basic statistics.

- Solid product fundamentals backlog management, stakeholder alignment, acceptance criteria.

- Excellent communication can explain algorithm behavior to non-technical stakeholders.