Exchange Optimization Lead Analyst

Summary

Join OpenX as a Lead Exchange Optimization Analyst and contribute to enhancing the efficiency and monetization of our global programmatic exchange. You will leverage your advanced SQL skills and data analysis expertise to diagnose inefficiencies, test hypotheses, and implement data-driven improvements. This role involves hands-on work with large datasets, designing and executing experiments, and collaborating with cross-functional teams. You will translate complex data findings into actionable recommendations and directly impact how billions of ad requests are processed. The ideal candidate possesses strong analytical skills, experience in a high-scale programmatic environment, and a passion for optimization. OpenX offers a cloud-based analytics stack, enabling rapid iteration from hypothesis to implementation.

Requirements

• 7+ years of experience in analytics, data operations, or optimization within a high-scale programmatic environment (SSP, DSP, or ad exchange)
• Expert-level SQL skills, especially in BigQuery or a similar large-scale data platform
• Strong background in data analysis, statistics, or experimentation—able to interpret noisy signals and guide decision-making with evidence
• Proven ability to break down complex systems, identify optimization levers, and implement data-driven strategies
• Demonstrated ability to manipulate, aggregate, and pivot large datasets for insight discovery
• Familiarity with OpenRTB, programmatic auction mechanics, and bidstream signals
• Clear communicator who can articulate technical findings to product managers, business leads, and engineers alike

Responsibilities

• Analyze large-scale exchange data (bid requests, impressions, wins, revenue) to surface actionable insights and optimization opportunities
• Design, execute, and evaluate experiments that test hypotheses around traffic shaping, bid filtering, pricing floors, or other monetization levers
• Develop and maintain dashboards and recurring reports in SQL and BI tools like Looker to monitor key exchange metrics and alert on anomalies
• Partner closely with product, engineering, and data science teams to refine exchange logic and build smarter systems for request routing, deal handling, and QPS allocation
• Work collaboratively across demand and supply teams to identify bottlenecks, inefficiencies, and growth opportunities
• Serve as an internal subject matter expert on bid request data quality, ad decisioning paths, and exchange performance drivers
• Translate complex data findings into clear narratives and strategic recommendations for cross-functional stakeholders

Preferred Qualifications

• Skilled in pivoting, aggregating, and slicing large datasets to identify patterns and anomalies
• Comfort with (and thrill of) exploratory data analysis and ad hoc and ongoing investigations in SQL-based environments
• Relentlessly curious about testing new ideas and concepts
• Strong ability to summarize and synthesize trends, findings and test results
• Experience with Excel/Google Sheets pivot tables, vlookups and other advanced features
• Advanced proficiency with Looker (or equivalent), including dashboard building
• Familiarity with OpenRTB specifications, bid request/response structure, and auction flows
• Understanding of SSP/DSP mechanics, including campaign delivery, win rates, QPS and traffic shaping
• Exposure to supply path optimization (SPO) concepts, ad quality signals (e.g., bcat, badv), and deal types
• Basic knowledge of identity frameworks (cookies, IPs, UID2, etc.) and how they impact optimization
• Awareness of request filters, throttling, floor pricing, traffic sets, and other monetization levers
• Heavy (expert level) SQL + to drive ideas to experimentation to analysis
• Comfort with BigQuery or similar large-scale analytics platforms (e.g., Snowflake, Redshift). Strong understanding of joins, UDFs, subqueries, CTEs, and performance tuning
• Familiarity with structuring analytical pipelines for analysis, learning and reporting
• Comfortable with scripting in Python, particularly for:Lightweight ETL or automationStatistical analysis (e.g., pandas, numpy, scipy)
• Bonus: Exposure to Airflow, GCP Dataform

Benefits

• A high-scale, cloud-native environment with full access to raw logs and preprocessed data views
• Sub-second query performance across billions of records using modern, scalable infrastructure
• End-to-end ownership: identify opportunities, run online experiments, and deploy successful changes to production within hours
• A culture that values business context, self-agency, and fast iteration over rigid process
• The chance to directly shape how one of the largest ad exchanges in the world operates, in real time
• $127,500 - $150,000 a year
• Medical, dental, vision, 401k, equity