Data Scientist - Pricing

Microsoft Microsoft · Big Tech · Redmond, WA +4 · Data Science

Data Scientist role focused on yield optimization for Azure infrastructure, developing machine learning models for pricing and resource allocation, and using causal inference to measure business impact. The role involves analyzing large datasets, collaborating with cross-functional teams, and staying current with AI and cloud economics trends.

What you'd actually do

  1. Develop machine learning models to optimize resource allocation and pricing strategies.
  2. Build causal inference models (e.g., difference-in-difference, synthetic control) to measure the impact of business decisions.
  3. Analyze large-scale datasets to identify patterns, trends, and opportunities for improving yield and efficiency.
  4. Partner with business planning, engineering, product management, and finance teams to align yield strategies with business objectives.
  5. Design and execute experiments to validate optimization hypotheses.

Skills

Required

  • Doctorate in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field
  • Python, R, or similar languages
  • Azure Machine Learning (ML) or equivalent cloud-based ML platforms
  • large-scale data and distributed systems
  • yield or revenue management, pricing optimization, or cloud resource allocation

Nice to have

  • 1+ year(s) data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results)

What the JD emphasized

  • Doctorate in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field
  • yield or revenue management, pricing optimization, or cloud resource allocation

Other signals

  • yield optimization
  • pricing strategies
  • resource utilization
  • cost efficiency
  • customer experience
  • machine learning models
  • causal inference