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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data Scientist - Payments (Inference) - **Company:** OpenX - **Location:** United States (Remote available) - **Experience:** Expert - **Salary:** $196,000.0 - $218,000.0 - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Airflow, Amazon Web Services, Architectural Patterns, Microsoft Azure, Python (Programming Language), Machine Learning, Tensorflow, Standard Sql, Workflow Management Systems, Cloud Platform System, Feature Engineering, Pytorch, Deep Learning, Data Strategy, Kubernetes, Information Technology, Machine Learning Operations, Programming Languages - **Published:** August 18, 2026 - **Apply:** https://www.workingnomads.com/job/go/1800424/ ## About the Role * 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 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, We understand and respect what each of us does. We are eager to teach and share what we know with others, both internally and externally. We are eager to learn from others and we ask questions internally and externally., Ideal team players are humble and demonstrate integrity. They put the team's success above their own, share credit generously, and value collective achievements. They are self-assured, open to coaching, and committed to continuous learning. DRIVEN Ideal team players are results-driven and motivated. They are curious, always seeking more to do, learn, and take on. As proactive problem-solvers, they take initiative without needing external motivation. They continuously think about the next steps and opportunities for improvement., Ideal team players are smart and possess the intellectual acumen to understand the complexities of our organization and industry. They are interpersonally intelligent, good communicators, and exemplify sound judgment in their interactions across the company to foster a collaborative environment. ## Description 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. 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., * 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, We take responsible risks and own and learn from our mistakes. We recognize and repeat success. We actively seek out and provide constructive feedback. We adapt quickly and embrace change. We tackle growth and learning with real urgency. We are endlessly curious. ## Related Videos - [Data Science in Retail](https://www.wearedevelopers.com/videos/586-data-science-in-retail) - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) - [Machine learning in the browser with TensorFlowjs](https://www.wearedevelopers.com/videos/155-machine-learning-in-the-browser-with-tensorflowjs) - [Photonic Computing: Programming a New Class of AI Accelerators (incl. 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