Staff Data Scientist, OpenX

• The ideal candidate brings deep expertise in applied machine learning, strong judgment in selecting methods for business problems at scale, and a track record of translating business needs into high-impact data science solutions
• Ph.D. in Data Science, Machine Learning, Computer Science, Physics, Mathematics, Operations Research, or related technical field with 6+ years of relevant industry experience; OR M.S./B.S. with 8+ years of relevant experience and a demonstrated track record of leading cross-team technical strategy and delivering organization-level impact
• Deep expertise in deep learning and broad fluency across the modern ML toolkit, with strong familiarity with optimization methods; additional experience in areas such as causal inference or experimentation design is a plus
• Proven ability to architect and deliver complex, production-grade ML systems that operate at scale
• Strong track record of nurturing DS/ML projects to maturity with significant business impact, including supporting and improving those systems beyond initial deployment
• Mastery of probability and statistics, especially techniques that scale to massive datasets
• Strong Python and SQL skills; experience with ML frameworks such as TensorFlow or PyTorch
• Strong communication and presentation skills, including proficiency in conveying complex technical concepts to both technical and non-technical audiences
• Track record of cross-team technical leadership and mentorship of senior data scientists and technical partners
• Experience working in digital media, marketing technology, or advertising technology — especially in marketplace, auction, or exchange systems

Desirable

• OpenX is seeking a Staff Data Scientist to join our Data Science team
• Our exchange processes hundreds of billions of ad requests daily and generates petabytes of data, requiring advanced machine learning, deep learning, and modern AI techniques delivered through scalable platforms to create value for customers
• A Staff Data Scientist is a senior technical leader whose impact spans multiple teams and business domains
• In this role, you will solve complex marketplace problems, set technical direction for your domain, architect major ML systems, mentor other scientists, and partner with engineering and product leaders on data-driven strategy
• Problems at this level include auction and marketplace optimization, bidding and yield strategy, relevance and prediction systems at exchange scale, causal measurement of marketplace changes, and capabilities for training, validating, and monitoring ML systems in production
• 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