Staff Data Scientist

Role Overview

• 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

Requirements

• 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

Tech Stack

• Python
• PyTorch
• SQL
• Tensorflow