| Microsoft Careers

Microsoft

Quick summary

Work type
On-site
Location
US
Salary
$102,100–$202,200 / yr
Posted
14 days ago
Closes
Nov 29, 2026

Market check

Salary context

Competitive pay

How this pay compares to similar roles

Similar $163k
This role $152k
$88k most similar roles pay here $234k

This role pays less than 65% of similar roles. Most pay $126,800–$199,850 — the shaded band above. At the midpoint, this role pays about $152k versus about $163k for comparable roles.

Based on 240 similar postings.

Employer

About Microsoft

Microsoft Corporation is a global technology leader producing software, hardware, and cloud services including Windows, Office 365, Azure cloud platform, Xbox gaming, and Surface devices. Industry: Software & Cloud Computing

Microsoft currently has 1578 open roles on FindRole.

Listed pay typically runs $119,800–$234,700 across 1406 roles with salary data.

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View all roles at Microsoft

At a glance

TL;DR · | Microsoft Careers

As a Data Scientist at Microsoft's Cloud and AI Platforms Monetization team, you will drive yield optimization strategies for Azure infrastructure by analyzing large-scale datasets to identify patterns and trends that enhance resource utilization and cost efficiency. Your day-to-day responsibilities include developing machine learning models to optimize pricing and resource allocation, collaborating with cross-functional teams such as engineering and finance to align monetization strategies with business goals, and conducting experiments to validate hypotheses using causal inference techniques. You will also create data visualizations for monitoring trends and translating insights into actionable recommendations. Ideal candidates possess a strong background in data science, mathematics, or related fields, along with experience in Python, R, Azure Machine Learning, and working with large-scale distributed systems. This role requires expertise in yield management, pricing optimization, and cloud resource allocation to address complex business challenges at scale.

What you'll do

  • Analyze large-scale datasets to identify patterns and trends for improving yield and efficiency.
  • Develop machine learning models to optimize resource allocation and pricing strategies.
  • Design and execute experiments using causal inference models to validate optimization hypotheses.
  • Create dashboards and visualizations to monitor business trends and translate findings into actionable insights.
  • Collaborate with cross-functional teams to align yield strategies with overall business objectives.

What we're looking for

  • Doctorate in a relevant field and 1+ year of data-science experience, or equivalent.
  • Master's degree with 2+ years of data-science experience, or equivalent.
  • Experience in Python, R, or similar languages.
  • Proficiency with Azure Machine Learning or comparable cloud-based ML platforms.
  • Expertise in working with large-scale data and distributed systems.
  • Background in yield management, pricing optimization, or cloud resource allocation.

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