Staff Data Scientist

Key Responsibilities:

Technical Leadership & Architecture
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
Execution & Strategy:
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
Mentorship & Influence:
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

Required Qualifications:

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

Desired Characteristics:

Experience developing, evaluating, or optimizing bidding algorithms for RTB environments.
Experience working with a cloud platform like GCP/AWS/Azure, with emphasis on GCP and the Vertex AI platform
Experience with ML pipeline and orchestration tools such as TFX, Kubeflow, or Airflow
Familiarity with other programming languages such as Java and Go
Experience working in digital media, marketing technology, or advertising technology — especially in marketplace, auction, or exchange systems
Track record of setting technical standards or best practices adopted beyond a single team
Experience representing data science capabilities or strategy in cross-functional forums