Senior/Staff Data Scientist

About Sovrn Every interesting company solves essential problems for other people. Sovrn is an Advertising Technology Software and Data business that helps Open Web businesses remain independent. We help them understand their business better, operate more efficiently, and make and keep more money. We believe in the freedom and free flow of information. We believe the Open Web is the largest source of this information. We believe in helping Open Web businesses remain Independent. Through Software platforms and Data solutions products, we help our customers: Understand their business better, so they can make better decisions. Operate their business more efficiently, so they can invest in what matters most. Make (and Keep) more money, so they control their own destiny. About the Role The Senior or Staff Data Scientist at Sovrn is a strategic technical leader who drives high-impact data initiatives across the organization. This role requires a unique blend of strategic vision ("the art of the possible") and tactical execution ("think and execute tactically"). You will solve ambiguous problems to deliver measurable business value and influence the future of data science in AdTech. You will guide architecture, experimentation, and product design while ensuring scientific and technical rigor. This position requires technical excellence, business acumen, and leadership. About the Job Operate at the frontier of applied AI as a hands-on practitioner — personally exploring, prototyping, evaluating, and deploying cutting-edge Agentic AI technologies to bring new, grounded insight into product, modeling, and optimization decisions. Design, implement, and deploy advanced predictive models, algorithms, and experiments that drive core business outcomes, specifically optimizing ad performance, user engagement, and monetization strategies. Analyze large-scale datasets to identify patterns, trends, and optimization opportunities, while maintaining and improving data pipelines and experimentation frameworks to support ongoing research. Define and evangelize best practices in modeling, testing, measurement, and data governance, ensuring scientific rigor while balancing practical business constraints and timelines. Collaborate cross-functionally to identify high-leverage AI/ML opportunities, translate them into actionable roadmaps, and deliver measurable outcomes. Mentor other data scientists through code review, experiment design, and technical feedback and model what it looks like to stay current with fast-moving AI research in a production-focused environment. Translate complex data problems into strategic decisions through compelling storytelling and clear communication of findings and recommendations to both technical and non-technical stakeholders. A successful candidate will have: Proven ability to deploy autonomous agents to production including optimizing inference performance, managing latency/cost tradeoffs, and ensuring robust model evaluation at each stage. Demonstrates prompt engineering discipline by systematically evaluating prompts across model families using quantitative evaluation. Active use of AI tools in daily technical work — integrates coding assistants, orchestration frameworks, and search-augmented workflows in ways that accelerate prototyping and reduce iteration cycles. Experience in data science and applied machine learning, with a strong record of delivering business impact. Deep technical proficiency across classical ML (supervised/unsupervised), reinforcement learning, and deep learning, with a strong foundation in statistical modeling, A/B testing, and causal inference. Proficiency with Python, SQL, cloud-based data ecosystems, modern AI/ML frameworks (e.g., Pandas, Scikit-Learn, PyTorch/TensorFlow, LangChain, Hugging Face, PydanticAI), experience with large-scale datasets and distributed computing frameworks (e.g., Spark, PySpark), and Databricks running on AWS Cloud. Strong understanding of ad tech ecosystems (e.g…