Principal Data Scientist

Microsoft

Confirmed live today High trust

Hybrid

Quick summary

Work type: Hybrid
Location: —
Salary: $142,800–$274,800 / yr
Posted: 13 days ago
Freshness: Confirmed live today
Closes: Apr 11, 2027

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $185k

This role $209k

$111k $292k

below market most similar roles pay here above market

This role pays more than 73% of similar roles. Most pay $154,512–$214,500 — the blue band above. At the midpoint, this role pays about $209k versus about $185k 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 694 open roles on FindRole.

Listed pay typically runs $119,800–$234,700 across 651 roles with salary data.

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At a glance

TL;DR · Principal Data Scientist

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JOB TITLE: Principal Data Scientist The Principal Data Scientist joins the MSN and Copilot Discover Business Analytics team to serve as a horizontal analytics partner across product, engineering, marketplace, and monetization organizations. This role involves translating complex data into actionable business recommendations, building forecasting and scenario-planning models for traffic and revenue, and developing frameworks that connect user behavior to monetization outcomes. You will leverage AI and machine learning solutions to automate insights and improve forecasting accuracy while evaluating tradeoffs between user experience and revenue. The position requires deep expertise in content ecosystems, digital advertising, and marketplace dynamics. Key competencies include managing structured and unstructured data, applying statistical techniques, and analyzing metrics like sessions, retention, and inventory utilization to influence strategic investments within AI-powered content discovery platforms.

What does a Data Scientist earn?

Median $173200 from 338 postings across 66 companies.

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Skills

Data Science Machine Learning AI Statistics Econometrics Forecasting scenario-planning Structured Data Unstructured Data Recommendation Systems Search Monetization Analytics Business Analytics Data-Driven Storytelling

What you'll do

Analyze user engagement, content consumption, marketplace dynamics, and revenue performance to identify growth opportunities.
Develop business frameworks connecting product initiatives, user behavior, content quality, and monetization outcomes.
Build forecasting and scenario-planning models for engagement, traffic, ad requests, and revenue.
Leverage AI and machine learning solutions to automate business insights and improve forecasting accuracy.
Evaluate tradeoffs between user experience, engagement, and monetization to support long-term business growth.
Translate complex data into clear business recommendations and data-driven stories for senior stakeholders.
Partner with cross-functional teams to shape strategy and investment decisions for product and marketplace initiatives.

What we're looking for

Doctorate in a quantitative field and 5+ years of data science experience, or Master's and 7+ years, or Bachelor's and 10+ years.
Equivalent experience to the degree and years of experience requirements.
Experience in content ecosystems, news feeds, recommendation systems, search, shopping, or content discovery platforms (preferred).
Experience partnering with advertising, monetization, or marketplace organizations (preferred).
Familiarity with engagement and monetization metrics like sessions, retention, RPM, and inventory utilization (preferred).
Experience leading analytics for large-scale consumer products with millions of users (preferred).
Demonstrated success influencing product strategy and business outcomes through data-driven insights (preferred).
Experience managing cross-functional initiatives involving Product, Engineering, Monetization, Marketplace, and Finance stakeholders (preferred).

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