Principal Data Scientist

Full Job Description

Define measurement frameworks used to evaluate strategic investments, prioritize opportunities, and assess product and business outcomes. Partner with Senior Directors and senior leaders to frame complex business questions and translate ambiguity into actionable decisions. Define success metrics, KPIs, and accountability mechanisms for critical initiatives. Influence product and business strategy through data-driven insights, analytical frameworks, and evidence-based recommendations. Develop reusable methodologies, analytical frameworks, and best practices that raise the quality bar across the organization. Communicate insights, risks, trade-offs, and recommendations to senior leadership. Mentor and guide data scientists through technical reviews, coaching, and thought leadership. Champion modern AI-assisted analytical workflows while maintaining solid scientific rigor and validation standards. Bachelor's Degree in Statistics, Data Science, Computer Science, Economics, Mathematics, Engineering, Operations Research, or a related field. 12+ years of experience in Data Science, Analytics, Applied Statistics, Economics, or related quantitative disciplines. Deep expertise in experimentation, A/B testing, statistical inference, causal analysis, forecasting, and metric design. Proven experience influencing high-impact product and business decisions through data and analytical insights. Experience designing measurement frameworks and success metrics for product, customer, and business outcomes. Solid programming skills in Python, SQL, R, or similar analytical languages. Excellent communication, collaboration, and stakeholder management skills. Experience supporting large-scale consumer products and services. Expertise in product analytics, customer measurement, engagement analysis, growth, retention, or monetization. Familiarity with Generative AI, Large Language Models (LLMs), and modern AI evaluation methodologies. Experience evaluating AI-powered experiences such as copilots, recommendation systems, search, or intelligent customer-facing products. Knowledge of Responsible AI principles and AI quality measurement frameworks. Experience with large-scale data platforms such as Spark, Cosmos, Hadoop, or cloud analytics environments. Join us in shaping the future of Windows through world-class decision science, experimentation, measurement, and AI evaluation. Develop scalable measurement systems and evaluation frameworks for products, features, and strategic initiatives. Establish best practices for experimentation, statistical rigor, metric development, and decision quality. Design and operationalize offline and online evaluation methodologies to assess quality, reliability, usefulness, and customer value.

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