Senior Economist

Discover the division's biggest opportunities to improve efficiency and help formalize them as scientific questions that can be answered with data and theory Estimate the causal effects of product, operational, and resource-allocation decisions on cost, utilization, customer outcomes, and revenue. Formulate resource allocation decisions as optimization problems Define measures that connect resource usage, including tokens, compute, and capacity, to productive utilization and business outcomes. Determine the appropriate micro-level unit of analysis, such as a feature, workflow, agent, or service, so that efficiency signals support actionable product and resource-allocation decisions. Work with product and engineering to instrument and collect the right data Translate analytical findings into decision rules, forecasting tools, and optimization systems; partner with business, product, and engineering teams to implement them and measure their realized impact. Write clear, accessible reports to communicate your analysis for executive consumption Bachelor's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 4+ years related experience (e.g., statistics predictive analytics, research) OR Master's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 3+ years related experience (e.g., statistics, predictive analytics, research) OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 1+ year(s) related experience (e.g., statistics, predictive analytics, research) OR equivalent experience. 4+ years of experience applying economics, statistics, causal inference, or optimization to complex business, policy, or product decisions. 3+ years of experience with scientific computing using R or Python, including frameworks such as Statsmodels, EconML, or DoubleML. Experience working with large-scale datasets and data processing tools to develop quantitative models, analyses, or research insights. 3+ years of experience conducting applied research in academic or industry settings, including formulating research questions and evaluating relevant literature. Doctorate in Economics or a related quantitative field preferred, particularly with a focus on applied microeconomics, econometrics, optimization, or causal inference. Demonstrated research impact through publications, patents, open-source libraries, or peer-reviewed academic work. Experience developing and deploying production systems or products, ideally across multiple stages of the product lifecycle from ideation through shipping. Knowledge of security-related domains, including threat intelligence, threat hunting, anti-fraud systems, and/or social engineering research. Strong written, verbal, and presentation skills, with the ability to translate complex technical or research concepts for a variety of audiences. Strong collaboration and partnership skills, with experience working across teams and guiding or mentoring less-experienced colleagues.