Data Scientist II

Working closely with product managers, engineers, and business partners, you will turn complex data into actionable recommendations that improve customer experiences and business outcomes. Develop scalable, high-performance analytics solutions and trusted data assets that enable data-driven decision-making. Work with development teams to improve instrumentation quality, partner with product stakeholders, build relevant datasets, define success metrics, create dashboards, scorecards, visualizations, and tools to democratize data and foster a data-driven culture. Execute targeted analyses to understand customer behavior, feature adoption, engagement, retention, and product impact. Collect requirements, create dashboards and report, and deliver actionable insights and recommendations to business and product teams. Utilize artificial intelligence and agentic development to improve data pipelines and analytics platforms, and leverage AI-powered tools to accelerate insight generation, improve

analytics productivity, and enhance data quality. Communicate analytical findings through presentations, written insights, and cross-functional collaboration, demonstrating teamwork and ownership. Take part in the on-call roster to monitor and mitigate data service degradation and downtime. Doctorate in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field OR Master’s Degree 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 consulting experience OR Bachelor’s Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 2+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results) OR equivalent experience. These requirements include but are not limited to the following specialized security screenings: Experience developing data and analytics solutions using cloud technologies such as Azure, Cosmos. Familiarity with scripting and query languages including PowerShell, KQL, and SQL, and programming languages such as C#, TypeScript, Python, or similar technologies. Experience analyzing product telemetry, defining metrics, and generating insights to support data-informed decision-making. Experience applying statistical analysis, experimentation, and product analytics to evaluate feature performance and customer engagement. Familiarity with AI-powered tools and agentic workflows to improve productivity, automate analysis, and accelerate insight generation. Familiarity with video creation and consumption technologies and industry trends is a plus. Committed to quality, including security, privacy, compliance, and performance. Ability to translate business questions into analytical approaches and communicate insights to technical and non-technical stakeholders