The Principal Applied Scientist role in the Signals Modeling team focuses on defining data-driven attribution and causal measurement methodologies for advertising systems. This position involves developing large-scale learning systems that enhance decision-making in ranking, bidding, and budget allocation. The team aims to transform engagement signals into reliable learning targets while addressing challenges like selection bias and delayed conversions. The role requires collaboration across research, engineering, and product leadership to implement advanced inference techniques at scale.

• Bachelor's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 6+ years related experience.
• Master's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 4+ years related experience.
• Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 3+ years related experience.
• Demonstrated track record of setting technical direction for large-scale machine learning or statistical systems.
• Deep expertise in causal inference, data-driven attribution, treatment effect estimation, or experimental design.

• Define and drive the scientific and technical strategy for data-driven attribution and causal measurement.
• Establish methodologies for incrementality estimation, counterfactual learning, and bias correction.
• Lead the design and production adoption of attribution and causal inference frameworks.
• Set evaluation standards that distinguish correlation from causation.
• Identify capability gaps and introduce advanced research or modeling approaches.
• Operate across organizational boundaries to align measurement strategy.
• Serve as a subject-matter expert and technical advisor on attribution and causal inference.
• Mentor scientists and influence technical direction to raise the organization’s scientific bar.

• Employees at Microsoft are often offered comprehensive, “world-class” benefits—including health and mental-wellness programs, competitive pay with bonuses and stock awards, and retirement/savings options. Time-off and flexibility are common, with generous vacation and holidays, parental and caregiver leave, and flexible work schedules, alongside learning support, employee resource groups, product discounts, and matching-gifts/volunteering programs. Specific benefits can vary by region.