| Microsoft Careers

Microsoft

Quick summary

Work type: On-site
Location: —
Salary: $142,800–$274,800 / yr
Posted: 26 days ago
Closes: Nov 11, 2026

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $180k

This role $209k

$101k most similar roles pay here $293k

This role pays more than 95% of similar roles. Most pay $152,150–$207,350 — the shaded band above. At the midpoint, this role pays about $209k versus about $180k for comparable roles.

Based on 238 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 1104 open roles on FindRole.

Listed pay typically runs $119,800–$234,700 across 986 roles with salary data.

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At a glance

TL;DR · | Microsoft Careers

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As a Principal Data Scientist at Microsoft, you will work closely with data engineering, product, field, and finance teams to transform large-scale telemetry into actionable insights, influencing product direction and executive decision-making. Your responsibilities include defining compensable metrics, designing quota models, and ensuring alignment between business objectives and model outputs. You will leverage Python, SQL Server, PySpark, and other tools like Hadoop, Apache Spark, CI/CD, Docker, Delta Lake, MLflow, Azure ML, and REST API development to build scalable data pipelines and machine learning models. With expertise in cloud platforms such as Azure Synapse and Azure Foundry, you will mentor junior data scientists and lead end-to-end ML lifecycle projects, ensuring ethical standards are met while driving innovation across product lines.

Skills

Python SQL PySpark Azure ML Apache Spark CI/CD Docker Delta Lake MLflow REST API Hadoop PowerBI SSAS Azure Synapse Azure Foundry Azure Cognitive Services Azure Databricks LangChain AutoGen Semantic Kernel

What you'll do

Defines quota-setting strategy aligned with business and customer objectives.
Partners cross-functionally to apply machine learning methods to quota design.
Leads project teams in troubleshooting issues by gathering data from multiple sources.
Oversees data acquisition, ensuring datasets are properly formatted and documented.
Conducts thorough reviews of analytical techniques to determine next steps.
Mentors engineers on ethical data handling and best practices for data cleaning.

What we're looking for

Doctorate in Data Science or related field with 8+ years of data-science experience.
10+ years of hands-on experience with cloud data platforms like Azure, AWS, or Google Cloud.
Extensive programming expertise in Python, SQL Server, and PySpark for scalable data pipelines and ML models.
Proven ability to translate business requirements into data-driven solutions using various ML algorithms.
Strong communication skills and proven track record of collaborating across cross-functional teams.
Experience managing stakeholder communications and leading end-to-end ML lifecycle projects.

Hybrid

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