Senior Economist – AI Strategy & Business Innovation team  

Design and apply causal inference methods to evaluate business initiatives in non-experimental settings. Identify, define, and quantify customer and business outcomes, then causally evaluate product and service offerings to determine which combinations maximize outcome attainment. Build robust analytical frameworks that connect customer, commercial, and operational signals to measurable outcomes. Develop cohort-level economic insights to support prioritization, investment decisions, and long-term planning. Partner with data and engineering teams to define practical data requirements and improve analytical readiness. Translate technical findings into clear, executive-ready recommendations. Raise analytical rigor across the organization through thought partnership, review, and coaching. Review analytical outputs from internal and external partners for methodological quality and clarity. Doctorate in Data Science, Mathematics, Statistics, Econometrics, Economics or related field AND 1+ year(s) of experience in applied economics or data-science (e.g., managing structured and unstructured data, applying statistical techniques and reporting results) OR Master's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics or related field AND 3+ years of experience in applied economics or data-science (e.g., managing structured and unstructured data, applying statistical techniques and reporting results) OR Bachelor's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics or related field AND 5+ years of experience in applied economics or data-science (e.g., managing structured and unstructured data, applying statistical techniques and reporting results) Doctorate in Data Science, Mathematics, Statistics, Econometrics, Economics or related field AND 3+ years of experience in applied economics or data-science (e.g., managing structured and unstructured data, applying statistical techniques and reporting results) OR Master's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics or related field AND 5+ years of experience in applied economics or data-science (e.g., managing structured and unstructured data, applying statistical techniques and reporting results) OR Bachelor's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics or related field AND 7+ years of experience in applied economics or data-science (e.g., managing structured and unstructured data, applying statistical techniques and reporting results) OR equivalent experience. 3+ years of experience applying causal inference in real-world settings Experience with quasi-experimental methods (DiD, IV, matching, regression techniques), experimentation and impact evaluation Demonstrated ability to communicate complex findings to business leaders and cross-functional partners, translating technical concepts into executive-ready messages is a critical competency- Familiarity with portfolio-level or risk modeling concepts, cost modeling under uncertainty Proven ability to work with messy, observational data and incomplete measurement systems Experience in SaaS / cloud services / platform economics, marketplace or pricing organizations, or experimentation teams (growth, product analytics) Exposure to operations, reliability, or capacity planning systems; AI-driven or automation-heavy environments - Familiarity with customer lifecycle, retention, and growth analytics. Experience influencing cross-functional teams in ambiguous, fast-moving environments.