Senior Economist

Microsoft Security's Economics and Analytics team provides rigorous scientific analyses that inform decisions on business strategy, product performance, and industry dynamics. We use a variety of tools, including experimentation, econometric analysis, machine learning, and economic theory to develop insights that drive executive action. We work on ambiguous, high-profile problems and bring a unique and valued perspective to the Security division.  

We are looking for a Senior Economist to join our team. This person will focus on the division’s operational efficiency. Example workstreams include helping to optimize GPU capacity; determining where we can use less expensive AI models for the same business outcomes; and creating insights on how we can organize and work more efficiently. The ideal candidate will have sharp economic intuition and deep technical skills combined with the gumption to start hacking away at difficult problems. Their crisp writing will give executives easy access to complex ideas. Does that sound like you? If so, please apply. 

Microsoft’s mission is to empower every person and every organization on the planet to achieve more. As employees we come together with a growth mindset, innovate to empower others, and collaborate to realize our shared goals. Each day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond. 

• 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.

Additional or Qreferred Qualifications

• 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.