Senior Data Scientist

Provides technical leadership for AI-native software engineering by driving adoption of Responsible AI practices, improving AI-enabled development processes, establishing engineering quality measures, mentoring teams on AI-assisted development, and ensuring AI-generated assets meet security, compliance, and quality standards. Owns architecture, engineering excellence, and software quality across complex products by leading system design, code quality strategies, testing frameworks, dependency management, performance optimization, security reviews, and scalable engineering practices while mentoring engineers across teams. Leads secure delivery, operational readiness, and platform reliability by defining deployment and rollback strategies, driving automation and observability, establishing security-by-design principles, managing experimentation frameworks, leading incident response and live-site operations, and ensuring products meet reliability, privacy, compliance, and disaster recovery requirements. Drives cross-team execution and customer-focused innovation by partnering with stakeholders to shape product requirements, align roadmaps, resolve dependencies, incorporate customer and telemetry insights, establish success metrics, and deliver secure, scalable, and highly available solutions that create measurable customer value. Doctorate in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 1+ year(s) data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results) OR Master's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 3+years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results) OR Bachelor's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND Doctorate in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 3+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results) OR Master's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field Experience with machine learning algorithms for forecasting, clustering, classification, recommendation systems, NLP, etc.