Data Analyst role in AdTech Product team focused on driving product strategy and optimization through data insights, experimentation, and performance analysis across advertising platforms. Responsibilities include analyzing large-scale advertising and campaign data, building dashboards and reports, partnering with Product Managers on feature evaluation, conducting deep-dive campaign analyses, monitoring auction dynamics and supply performance, performing fraud detection, conducting funnel and cohort analyses, supporting forecasting and revenue optimization, collaborating on data requirements, and translating data findings into recommendations. Required skills: Bachelor's degree in quantitative field, 2+ years experience in analytics roles within AdTech or related industries, strong SQL proficiency, experience with BI tools (Tableau, Power BI, Looker, Metabase), understanding of statistical concepts and experimentation, strong analytical and communication skills. Preferred qualifications include experience with DSPs, SSPs, programmatic platforms, digital advertising metrics, mobile advertising ecosystems, data warehouses (BigQuery, Snowflake, Redshift, Databricks), and knowledge of machine learning concepts.
What you'll do
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Bellevue, United States; Boston, United States; Boulder, United States; Chicago, United States; Denver, United States; Los Angeles, United States; New York, US; San Francisco, United States; San Jose, United States; Seattle, United States; Ventura, United States•7 days ago
Analyze large-scale advertising, user, campaign, auction, and supply-side datasets to identify performance trends, revenue opportunities, product gaps, and optimization initiatives
Build and maintain dashboards, automated reports, anomaly detection systems, and performance monitoring frameworks that provide timely and actionable insights to Product, Commercial, Operations, and Executive teams
Partner closely with Product Managers to evaluate feature performance, measure business impact, prioritize product enhancements, and support data-driven roadmap decisions
Conduct deep-dive analyses on campaign performance to identify optimization opportunities across targeting, bidding strategies, budget allocation, audience segmentation, creatives, inventory sources, and conversion performance
Analyze auction dynamics and bidding behavior, including bid density, win rates, clearing prices, supply quality, and marketplace competitiveness to improve DSP efficiency and advertiser outcomes
Monitor and optimize supply performance by evaluating inventory quality, publisher effectiveness, traffic patterns, viewability, engagement metrics, and monetization efficiency across supply partners
Perform fraud detection and traffic quality analysis by identifying invalid traffic (IVT), click fraud, bot activity, domain spoofing, ad stacking, abnormal user behavior, and other forms of advertising fraud; partner with Engineering and Operations teams to implement mitigation strategies and improve platform trust and safety
Conduct funnel analysis, cohort analysis, attribution analysis, audience analysis, and user segmentation to uncover growth opportunities, retention drivers, and advertiser success factors
Support forecasting, business planning, and revenue optimization initiatives through quantitative analysis
Collaborate with Engineering and Data teams to define data requirements, event tracking, and measurement frameworks
Translate complex data findings into clear recommendations for technical and non-technical stakeholders
Requirements
Bachelor's degree in Engineering, Statistics, Mathematics, Economics, Computer Science, or a related quantitative field
2+ years of experience in Product Analytics, Business Analytics, Data Analytics or a similar role within AdTech, MarTech, Digital Advertising, or Internet companies
Strong proficiency in SQL with experience handling large datasets
Experience with BI and visualization tools such as Tableau, Power BI, Looker, or Metabase
Strong understanding of statistical concepts, experimentation methodologies, and hypothesis testing
Excellent analytical thinking and problem-solving skills
Strong communication skills with the ability to influence product decisions using data
