OpenX

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

Senior Business Intelligence Data Analyst

Operations

• Provide Level 1–3 support across all IT platforms with a strong focus on Mac, Windows, SaaS (Google Workspace, MS365), and MDM (Jamf/InTune)
• Visit the office and perform infrastructure quality checks on-site at least once a week OR on-demand (Currently most people visit the office on Tuesdays/Wednesdays)
• Own and coordinate endpoint and peripheral procurement, imaging, deployment, inventory documentation and lifecycle management globally
• Proactively monitor systems, logs, and user behaviors to identify and prevent issues before they are reported
• Document and maintain clear Open/In Progress/Completed task status in our team tools.
• Act as escalation point for IT to our stakeholders on best practices, ownership, and structured troubleshooting
• Participate in IT projects including migrations, automation tooling, system integrations, and vendor transitions
• Support weekly IT onboarding sessions, with a focus on automation and user-readiness.
• Process offboarding sessions along with the hardware retrieval process, preparing to repurpose devices etc.
• Deliver VIP support and ensure a calm, helpful demeanor under pressure
• Quickly reprioritize tasks and shift focus ad-hoc in response to urgent business needs
• Maintain tidy, functional, and documented workspaces, whether physical or digital
• Provide cross-functional support in collaboration with Security, Engineering, People Ops, and OfficeOps
• Apply structured thinking to analyze and connect related incidents
• Contribute to and maintain internal documentation (SOPs, runbooks, FAQs)
• Operate within and improve existing ITIL-aligned practices: incident, change, and problem management
• Experience with Google Meet hardware (setup, troubleshooting, and support)
• Practical experience using Gemini and/or Claude in day-to-day IT support and documentation

IT Operations Specialist – III

• Architect robust, scalable, and maintainable ML systems for broad use across the exchange, spanning training pipelines, real-time inference, validation, and monitoring
• Serve as a go-to expert in deep learning and related advanced data science domains, with the breadth to guide method selection across adjacent areas
• Lead the evaluation and adoption of new AI/ML modeling techniques, frameworks, and research advancements relevant to OpenX’s marketplace problems
• Define and evolve technical standards and best practices within their domain, influencing broader adoption across the organization
• Identify and lead high-impact, cross-team data science initiatives, such as improving bidding strategies, building new prediction systems, or redesigning experimentation frameworks
• In partnership with engineering and product leadership, drive the data science roadmap for a product area or platform capability
• Partner with product managers and commercial stakeholders to translate marketplace problems into data science solutions with measurable business outcomes
• Solve novel, ambiguous problems requiring innovation in methodology, algorithms, or feature engineering
• Mentor and develop senior data scientists, helping them grow toward broader technical leadership
• Raise the skills, impact, and scientific rigor of teams around them through guidance, architectural patterns, and strategic direction
• Communicate technical strategy and build consensus for complex decisions across senior leadership and cross-functional teams

Staff Data Scientist

• Build performance and revenue reporting tools for internal customers
• Help build and automate data and reporting processes for the Finance organization
• Ad-hoc analysis and reporting, serving teams across the company
• 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

Business Intelligence Data Analyst

Sales

• Partner with Leadership to design and model sales incentive plans aligned to business strategy. Conduct scenario modeling and cost simulations to evaluate plan effectiveness and financial impact.
• Lead the end-to-end management of the quarterly incentive compensation cycles, ensuring accurate attainment calculations, rigorous data validation, and timely, error-free payout delivery.
• Establish and maintain governance across all data sources (e.g. CRM, data warehouse, incentive tools) ensuring consistency and resolving discrepancies across quota attainments, MBO attainments and payout calculations.
• In partnership with Commercial Leadership, Rev Ops leadership, People Leadership and Finance leadership, serve as the subject matter expert on sales incentive plans providing guidance to commercial leaders and employees. Lead the operationalization of quota setting, territory management, and MBO frameworks.
• Develop and enforce a robust change control process for all related updates, including quota adjustments and exception handling. Ensure full documentation and compliance with internal controls and audit requirements.
• Serves as the point of accountability for resolving program related inquiries and discrepancies. Leads the cross-functional resolution efforts, maintaining issue tracking, and driving timely , transparent outcomes.
• Own dashboard and reporting framework in partnership with Revenue Operations, to monitor attainment accuracy, payout progress, and operational efficiency.
• Prepare and deliver program summaries, committee materials, and approval communications. Translate complex data into clear, concise insights for senior leadership and stakeholders.
• Partner with CRM, data and product teams to enhance system integrations, automate workflows, and improve scalability and reliability of program processes.
• Own and maintain comprehensive documentation, including SOP’s, RACIs, and procedures ensuring consistency, transparency, and operational continuity.
• Lead quarterly retrospectives and process reviews to identify inefficiencies, data gaps, and communication challenges. Drive continuous improvement initiatives across tools, process, and governance frameworks.

Senior Sales Incentive Program Manager

Business Development Rep

• Identify and research prospective publisher partners across CTV, mobile app, and web**• Analyze publisher business models, ownership structures, and monetization strategies**• Support pipeline development and track new business opportunities**• Prepare meeting briefs, opportunity summaries, and follow-up materials**• Partner cross-functionally with Account Management, Marketing, and Product teams**• Conduct industry and competitive research across the programmatic ecosystem**• Contribute to strategic projects including market expansion and publisher segmentation**• Present insights and recommendations to the Publisher Development team