Principal Applied Scientist (AI)

TL;DR

Principal Applied Scientist (AI): Defining and driving the scientific and technical strategy for data-driven attribution and causal measurement across advertising systems with an accent on incrementality estimation, counterfactual learning, delayed-feedback modeling, and bias correction. Focus on leading the design and production adoption of causal inference frameworks at web scale and setting evaluation standards for experimental rigor.

Location: Redmond, United States (Hybrid). Employees living within a 50-mile commute of a designated Microsoft office in the U.S. are expected to work from the office at least four days per week.

Salary: USD $139,900 – $274,800 per year (typical U.S.); USD $188,000 – $304,200 per year (San Francisco Bay area and New York City metropolitan area)

Company

hirify.global is a division of Microsoft that builds intelligence powering advertising marketplaces by understanding user behavior, measuring impact, and optimizing outcomes.

What you will do

• Define and drive the scientific and technical strategy for data-driven attribution and causal measurement across advertising systems.
• Establish methodologies for incrementality estimation, counterfactual learning, delayed-feedback modeling, and bias correction.
• Lead the design and production adoption of attribution and causal inference frameworks to improve bidding, ranking, and advertiser ROI at web scale.
• Set evaluation standards that distinguish correlation from causation and elevate experimental rigor across teams.
• Identify capability gaps and introduce advanced research, tools, or modeling approaches to strengthen measurement foundations.
• Mentor scientists and influence technical direction to raise the organization’s scientific bar.

Requirements

• Bachelor’s Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or a related field AND 6+ years related experience (e.g., statistics, predictive analytics, research).
• Recognized expertise in attribution, incrementality, marketplace experimentation, or causal ML.
• Track record of driving multi-year research or modeling agendas that materially improved product outcomes.
• Experience defining measurement strategy for advertising platforms, marketplaces, or large-scale recommendation systems.
• Deep expertise in causal inference, data-driven attribution, treatment effect estimation, counterfactual learning, or experimental design – applied in production environments.
• Significant experience developing and deploying production ML systems across multiple stages of the product lifecycle.

Culture & Benefits

• Mission to empower every person and every organization on the planet to achieve more.
• Culture of inclusion, growth mindset, innovation, respect, integrity, and accountability.
• Opportunity to influence director- or VP-level technical strategy.
• Access to comprehensive benefits and compensation.