OpenX

Vice President

• Build, maintain, and own executive and leadership level relationships with key publishers including regular touchpoints both virtually and in-person.
• Develop mid-to-long-term strategy for the global publisher business including owning go to market, regional revenue targets, managing P&L, and planning headcount.
• Establish OpenX as a thought leader by maintaining a strong command of key industry topics such as curation, inventory quality, AI, supply path optimization (SPO), connected TV (CTV), and privacy-first solutions.
• Serve as a senior spokesperson for OpenX, representing the company at industry events, panels, and with key stakeholders across the programmatic ecosystem.
• Lead and develop a collaborative, high-performing team across business development and account management within the ad-tech ecosystem, providing strategic direction, clear goals, coaching, and professional development. Foster a culture of ownership, continuous learning, and thoughtful execution to drive revenue growth, strengthen publisher relationships, and deliver innovative, data-driven monetization solutions.
• Drive the new supply pipeline across CTV, web, in-app, digital out-of-home (DOOH), and audio publishers.
• Prospect and close strategic partners in emerging verticals such as retail media, gaming platforms, AI-driven applications, ride-share, and fitness technology.
• Provide strategic market intelligence to inform OpenX’s product roadmap and go-to-market strategy, ensuring alignment with evolving publisher and buyer needs.
• Leverage and implement AI workflows and automation to enhance operational efficiency and improve customer service for publisher partners.
• Partner closely with buy-side commercial teams to support strategic SPO engagements and pitches, and to increase overall deal share of upfronts, PG’s, and PMP’s.

SVP, Global Publisher Development

DevOps Engineer

• Design, write and deliver software to implement and support large web-scale, highly-performant, highly-available infrastructure on GCP/AWS (e.g. Terraform)
• Monitor infrastructure, respond to incidents, correct and improve systems to prevent incidents, and plan capacity
• Support system deployments and product releases
• Tune large-scale clusters for optimal performance and efficiency
• Work closely with engineering, project management, and operational peers to develop innovative technical tools and solutions
• Participation in on-call rotation

Site Reliability Engineer – IV

Data Scientist

• Own the end-to-end data science lifecycle for moderately complex models and significant project components — spanning data ingestion, feature engineering, modeling, validation, deployment, monitoring, and retraining.
• Apply expertise across several core areas of machine learning and statistics (e.g., gradient-boosted models, deep neural networks, time series, causal inference concepts, experimentation design), selecting appropriate methods for complex data science problems.
• Write efficient, modular, well-tested code for data processing, feature engineering, and model training/inference, leveraging distributed tooling (e.g., Vertex AI pipelines, Dataflow, BigQuery) where appropriate.
• Design and implement robust validation frameworks for complex experiments and models, accounting for potential biases and real-world performance.
• Troubleshoot complex model performance issues, data anomalies, and code bugs effectively with little guidance.
• Define analytical approaches and scope data science projects for moderately complex or ambiguous business problems.
• Partner with product managers and stakeholders to define success metrics and experiment goals, and to translate marketplace problems into data science solutions.
• Lead the design and analysis of experiments (e.g., A/B tests, switchback) for your projects, and interpret complex model results and experimental outcomes with a focus on actionable insights and business outcomes.
• Proactively identify opportunities within your domain where data science can provide significant value, and initiate exploration.
• Follow and help improve established team processes for coding standards, documentation, reproducibility, and experimentation.
• Mentor DS I and DS II scientists, providing technical guidance, reviewing code, analyses, and models, and supporting their growth in analytical and modeling skills.
• Influence technical decisions within the team regarding modeling choices, validation strategies, and tooling through well-reasoned arguments and expertise.
• Drive improvements to team standards, data science best practices, and analytical rigor; take ownership of specific team practices or technical components (e.g., a feature store component, leading experimentation reviews).
• Educate stakeholders on the capabilities and limitations of data science models, and clearly explain complex methodologies and findings to both technical and non-technical audiences.
• Participate actively in recruiting, providing high-quality, graded interview feedback for candidates up to this level.

Data Scientist III

Data Analyst

• Own and scale performance and revenue reporting tools for internal customers to drive data-informed decisions
• Lead automation and optimization of Finance data pipelines and reporting processes
• Deliver impactful ad-hoc analysis and reporting to support teams across the company
• Develop, lead, and execute deep dive quantitative analyses that translates data into actionable insights
• Provide analytical and decision-making support for key company initiatives
• Present analysis and share findings with both technical and non-technical stakeholders

SVP, Global Publisher Development

Site Reliability Engineer – IV

Data Scientist III

Senior Business Intelligence Data Analyst