Applied Scientist II

Microsoft

Hybrid

Quick summary

Work type: Hybrid
Location: —
Salary: $102,100–$202,200 / yr
Posted: 15 days ago
Closes: Dec 9, 2026

Market check

Salary context

Below market

How this pay compares to similar roles

Similar $181k

This role $152k

$87k most similar roles pay here $244k

This role pays less than 72% of similar roles. Most pay $133,251–$229,025 — the shaded band above. At the midpoint, this role pays about $152k versus about $181k 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 622 open roles on FindRole.

Listed pay typically runs $119,800–$234,700 across 571 roles with salary data.

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At a glance

TL;DR · Applied Scientist II

Role Posting Log in to save

Join our Applied Scientist team as an expert in Machine Learning, Generative AI, and Agentic Modeling to drive innovation for Bing and Consumer Copilot by advancing generative search experiences through cutting-edge AI technologies. Your daily tasks will include building and maintaining production machine learning models, working with state-of-the-art large language models like Qwen and Llama, and conducting data-driven experiments to extract actionable insights from petabyte-scale datasets using tools such as Python, C#, R, Java, and SQL. You’ll need hands-on experience in generative modeling, prompt tuning, and model optimization, along with a strong background in statistics or computer science, ideally at the master’s level or higher, complemented by proficiency in programming languages like Python and C++.

Skills

Python C# Java SQL R C++ Scala NLP Machine Learning Data Mining Feature Engineering Statistical Techniques Regression Classification Optimization Generative Models Large Language Models Petabyte Scale Data Processing Experiment Design Hypothesis Testing Actionable Insights Concise Reporting

What you'll do

Build and maintain production ML models to enhance performance outcomes.
Conduct hands-on work with state-of-the-art generative AI models like Qwen and Llama.
Analyze large-scale datasets using advanced techniques such as regression, classification, and NLP.
Design experiments, interpret data results, and derive actionable insights for business decisions.
Handle petabyte-scale data efficiently using a variety of tools and programming languages.

What we're looking for

Master's degree in relevant field plus 1 year of experience or equivalent.
Doctorate in Statistics, Computer Science, Electrical Engineering, or related field.
Proficient in programming languages like Python, C#, Java, and Scala.
Experience with large-scale data wrangling and analysis using various tools.
Hands-on expertise in building and optimizing production machine learning models.
Strong background in machine learning, feature engineering, and statistical techniques.

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