Microsoft Senior Applied Scientist 

United States, Washington 

807664478

Online Advertising is one of the fastest growing businesses on the Internet today - serving hundreds of millions of ad impressions per day and generating terabytes of user events data every day.The rapid growth of online advertising has created enormous opportunities as well as technical challenges that demand computational intelligence.

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The Bing Ads Understanding team is at the center stage of this exciting new interdisciplinary field that involves natural language processing, machine learning, data mining, and statistics, to solve challenging problems that arise in online advertising. The central problem of computational advertising is to select an optimized slate of relevant ads for a user to maximize a total utility function that captures the expected revenue, user experience and return on investment for advertisers.

We are a world-class Research and Development (R&D) team of dedicated and talented scientists and engineers who aspire to solve tough problems and turn innovative ideas into high-quality products and services. We help hundreds of millions of users find what they want, and advertisers gain the right audience, thereby directlyour business as a Marketplace.

Microsoft’s mission is to empower every person and every organization on the planet to achieve more. As employees we come together with a growth mindset, innovate to empower others, and collaborate to realize our shared goals. Each day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond.

Required Qualifications:

• 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.
• 3+ year experience delivering, scaling, andmaintaininghighly successfuland innovative machine learning products with your fingerprints all over them.

Preferred Qualifications:

• Proven experience in algorithm development and analytical background andvery goodunderstanding on how to apply advanced knowledge to solve real problems.
• Ability to work independently in a team to deliver innovative solutions solving challenging business/technical problems from high level vision and architecture, down to quality design and implementation.
• Have good understanding ofstate-of-the-artmachine learning and deep learning technologies. In particular, hands-on experiences with deep learning models (DNN, Attention, CNN, RNN) and frameworks (TensorFlow,PyTorch,Keras, etc.) will bevery helpful.
• Experience in parallel or distributed processing, high performance computing, stream computing and SCOPE.
• Self-motivated and self-directedand beable to work constructively with a wide variety of people, team and changing business priorities.
• Demonstratedexperience working with LLMs, such as GPT, BERT, or similar models, including knowledge of their strengths, limitations, and capabilities.
• In-depth knowledge of natural language processing (NLP) techniques and concepts, including tokenization, semantic analysis, and text generation.

Applied Sciences IC4 - The typical base pay range for this role across the U.S. is USD $117,200 - $229,200 per year. There is a different range applicable to specific work locations, within the San Francisco Bay area and New York City metropolitan area, and the base pay range for this role in those locations is USD $153,600 - $250,200 per year.Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here:

Microsoft will accept applications for the role until September 16, 2024.

• Building andmaintainingproduction machine learning models to generate text assets and predict ad quality.
• Finding insights and forming hypothesis on web-scale data with various machine learning, feature engineering, statistical, and data mining techniques:e.g.regression, classification, Natural Language Processing (NLP), optimization, p-valuesanalysis.
• Designing experiments, understanding the resulting data, and producing actionable, trustworthy conclusions from them.
• Crafting and Optimizing Prompts for Effective Large Language Models (LLM) Performance: Design, test, and refine prompts to elicitaccurate, 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.
• Wranglinglarge amountsof data (think petabytes) using various tools, including open-source ones and your own. All programming languages are welcome, especially Python, R, C#, C++, Java, andSQL.
• Taking complex problems and the associated data and giving the answers in a concise form toassistsenior executives in making key business decisions.
• Embody our