| Microsoft Careers

Microsoft

Hybrid

Quick summary

Work type
Hybrid
Location
WA
Salary
$142,800–$274,800 / yr
Posted
11 days ago
Closes
Dec 1, 2026

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $194k
This role $209k
$127k most similar roles pay here $291k

This role pays more than 69% of similar roles. Most pay $173,200–$214,712 — the shaded band above. At the midpoint, this role pays about $209k versus about $194k 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 1580 open roles on FindRole.

Listed pay typically runs $119,800–$234,700 across 1408 roles with salary data.

Most-posted roles

View all roles at Microsoft

At a glance

TL;DR · | Microsoft Careers

As a Partner, Data Science & Analytics at Microsoft AI’s Ecosystem Data Science Team, you will lead the development of cross-product measurement strategies and drive technical excellence through mentorship and collaboration with product, engineering, and business teams. Your daily tasks include applying machine learning and statistical modeling to large datasets, designing experiments for user and demand dimensions, and optimizing performance across products. You will leverage advanced analytics tools such as Python, SQL, and R to deliver actionable insights that enhance user experience and business value. This role requires expertise in data science techniques, a strong background in mathematics or statistics, and the ability to work in a dynamic environment where you can challenge the status quo and solve ambiguous problems with data-driven solutions.

What you'll do

  • Lead the development of ecosystem data strategies for marketplace performance.
  • Apply machine learning and statistical modeling to large datasets for accurate metric measurement.
  • Design and execute experiments across user dimensions to optimize product outcomes.
  • Identify opportunities for process improvement and implement data-driven solutions.
  • Develop standardized processes for data acquisition and operationalizing ML models.
  • Engage stakeholders with actionable insights and make independent decisions for the team.

What we're looking for

  • Extensive experience in data science and analytics, including managing structured and unstructured data.
  • Strong background in statistical techniques, machine learning, and data mining for large datasets.
  • Proven ability to design and execute experiments, translating strategies into actionable plans.
  • Leadership skills to mentor data scientists and drive technical excellence across teams.
  • Experience in developing and standardizing processes for data acquisition and operationalizing ML models.
  • Ability to collaborate closely with product, engineering, and business teams on data science solutions.
  • Strong influence and decision-making skills to engage stakeholders with compelling insights.

More like this

Similar roles

| Microsoft Careers

Microsoft

US 101 days ago $165,600$296,400
Python R MATLAB C# Java Machine Learning Statistical Modeling Experiment Design SQL CI/CD Azure AWS Kubernetes Docker Git Jupyter Notebook Tableau Power BI PostgreSQL MSSQL

Principal Data Scientist | Microsoft Careers

Microsoft

US 126 days ago $139,900$274,800
Python SQL MachineLearning StatisticalAnalysis DataVisualization AWS Azure CI/CD Git Scikit-learn Pandas NumPy TensorFlow Keras ResponsibleAI DataEngineering AgenticAISolutions MicrosoftProducts

Associate Principal, Data Analytics Engineering

The OCC

Chicago 97 days ago $103,400$177,600
Python SQL Tableau AWS Airflow Git Agile Pandas Numpy R Matlab REST APIs CI/CD PostgreSQL Alteryx Power BI Unix Curator Generative AI Prompt Engineering
Hybrid

| Microsoft Careers

Microsoft

US 103 days ago $142,800$274,800
SQL Azure SQL Database Power BI Excel Dynamics 365 ACM SIGMOD VLDB IEEE ICDE Machine Learning Artificial Intelligence Cloud Platforms Distributed Systems Resource Management Low-code Data Transformations Modern Hardware CI/CD