Applied Scientist II and Senior Applied Scientist Job at Microsoft Corporation (Redmond)

Applied Scientist II and Senior Applied Scientist

Microsoft Corporation

Location:
United States , Redmond

Category:
IT - Software Development

Contract Type:
Not provided

Salary:

100600.00 - 199000.00 USD / Year

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Job Description:

Come build community, explore your passions and do your best work at Microsoft. This opportunity will allow you to bring your aspirations, talent, potential - and excitement for the journey ahead. Monetization at Microsoft AI is at the forefront of one of the fastest growing areas on the Internet—online advertising and intelligent monetization solutions. Our work powers products like Bing Ads, Copilot, and the broader Microsoft ecosystem, serving billions of ad impressions and generating terabytes of user interaction data every day. The rapid evolution of this space presents incredible opportunities and complex technical challenges that require cutting-edge solutions in machine learning, natural language processing, data mining, and large-scale optimization. A PhD is preferred for this role, as it reflects advanced proficiency in scientific methodology, rigorous experimental design, and a strong commitment to reproducible research practices. We are a world-class organization of passionate scientists and engineers working at the intersection of AI and monetization. Our mission is to select and deliver optimized, personalized content and ads across Microsoft surfaces to maximize a total utility function that balances revenue, user experience, and advertiser value. Whether it's helping users discover what they need, enabling advertisers to reach their ideal audience, or infusing intelligence into Copilot interactions, we are redefining what’s possible in the future of monetization through AI.

Job Responsibility:

Building and maintaining production machine learning models for ad retrieval, quality prediction and creative generation
Finding insights and forming hypothesis on web-scale data with various machine learning, feature engineering, statistical, and data mining techniques: e.g. regression, classification, NLP, optimization, p-values analysis
Designing experiments, understanding the resulting data, and producing actionable, trustworthy conclusions from them
Craft and Optimize Prompts for Effective LLM Performance: Design, test, and refine prompts to elicit accurate, relevant, and useful responses from LLMs. This involves understanding the nuances of how the model interprets different inputs, experimenting with various prompt formulations, and iterating based on performance metrics and user feedback
Wrangling large amounts of data (think petabytes) using various tools, including open-source ones and your own. All programming languages are welcome, especially Python, R, C#, C++, Java, and SQL
Taking complex problems and the associated data and giving the answers in a concise form to assist senior executives in making key business decision

Requirements:

Bachelor's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 2+ years related experience (e.g., statistics, predictive analytics, research) OR Master's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 1+ year(s) related experience (e.g., statistics, predictive analytics, research) OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field OR equivalent experience
2+ years experience delivering, scaling, and maintaining highly successful and innovative machine learning products
1+ year(s) experience creating publications (e.g., patents, peer-reviewed academic papers)
Experience with Large Language Models: Demonstrated experience working with LLMs, such as GPT, BERT, or similar models, including knowledge of their strengths, limitations, and capabilities
Understanding of NLP: In-depth knowledge of natural language processing (NLP) techniques and concepts, including tokenization, semantic analysis, and text generation
Understanding of state-of-the-art machine learning and deep learning technologies. In particular, hands-on experiences with deep learning models (DNN, Attention, CNN, RNN) and frameworks (TensorFlow, PyTorch, Keras, etc.)
Algorithmic and analytical background and understanding on how to apply advanced knowledge to solve real problems
Experience in parallel or distributed processing, high performance computing, stream computing and SCOPE

Nice to have:

Bachelor's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 4+ years related experience (e.g., statistics predictive analytics, research) OR Master's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 3+ years related experience (e.g., statistics, predictive analytics, research) OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 1+ year(s) related experience (e.g., statistics, predictive analytics, research) OR equivalent experience

Additional Information:

Job Posted:
March 21, 2026

Employment Type:

Fulltime

Work Type:

Hybrid work

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