Data Analysis & Evaluation Dataset Development Write efficient, readable code in Python, SQL, KQL, or similar languages to prepare and analyze large-scale datasets, including customer feedback, text, and consented multimodal logs. Build representative evaluation datasets across enterprise and consumer scenarios, including information retrieval, text creation and editing, image and file workflows, shopping, education, coding, technical support, health, sports, news, and finance. Design evaluation coverage for text and voice inputs, single- and multi-turn conversations, and location- or geography-sensitive prompts. Partner with engineering, product management, and applied science teams to define measurement strategies and inform product decisions. Contribute to response-quality side-by-side evaluations by designing studies and rubrics, analyzing results, and assessing statistical and practical significance. Develop decision-relevant metrics, dashboards, and compelling narratives that translate analyses into actionable product recommendations. Stay current with AI offerings and competitive developments, using data and evaluation results to identify feature gaps and opportunities. Provide mentorship through analytical code reviews, study-design guidance, innovation, and sharing data science best practices. Embody our culture and values. 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) These requirements include but are not limited to the following specialized security screenings: 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 AND 6+ 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 8+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results) OR equivalent experience. 4+ years of experience using Python, SQL, KQL, R, or similar languages to analyze large-scale structured and unstructured datasets. Experience driving effective cross-organizational communication, end-to-end analytical problem solving, collaboration, customer focus, and the ability to navigate ambiguity. Demonstrated ability to communicate technical details clearly across organizational boundaries. Demonstrated ability to work end to end in complex analytical problem domains, from problem definition and study design through execution, interpretation, and communication of results. Customer Obsession: Customer- and metrics-driven approach to evaluation, experimentation, and product decision-making. Growth Mindset: Demonstrated ability and motivation to learn, enter new domains, and manage through ambiguity.