Drive optimizations across Publisher network by leveraging complex datasets, machine learning methods, and statistical modeling to identify optimization opportunities, improve bidding efficiency and deliver actionable insights.
Requirements
- Strong knowledge of adtech ecosystems, including header bidding, SSPs, DSPs, GAM, Identity Providers
- Deep familiarity with yield levers such as floors, caching, timeouts, auction dynamics
- Expert in SQL and experience with large scale data processing such as BiqQuery.
- Familiarity with data visualization tools (e.g., Tableau, Looker, or similar) and ability to tell compelling stories with data.
- Experience designing and analyzing A/B tests; familiarity with machine learning techniques and LLMs is a plus.
Responsibilities
- Analyze large-scale eventstream and auction data to uncover trends, anomalies, and optimization opportunities.
- Design, test, and implement data-driven strategies for improving publisher yield, bidding dynamics, and revenue outcomes.
- Build and maintain monitoring and alerting for performance and diagnostic issues.
- Lead automating systems and data processes.
- Support A/B testing frameworks as needed.
- Develop predictive models and algorithms to forecast key metrics.
- Conduct root cause analyses for data quality, ad-serving, or system issues, ensuring data integrity and reliable reporting.
Other
- Must have minimum 2 years of experience in adtech; with at least 2 years in an analytical or data science role
- Advanced skills in Excel and Google Sheets.
- Strong communication skills for translating complex technical findings into actionable recommendations.
- Highly organized, proactive, and adaptable to a fast-changing industry landscape.
- This role is not eligible for visa sponsorship
