Senior Applied Scientist-Ads

Microsoft Audience Network (MSAN) part of the Microsoft AI (Artificial Intelligence) is seeking  a Senior Applied Scientist-Ads.

This role is available in Redmond, WA or Mountain View, CA.

This is an exceptional opportunity to apply your advanced skills in one of the fastest-growing businesses, to solve real-world problems on a scale. Our goal at MSAN is to maximize value for users and advertisers through our platform. 

As the Senior Applied Scientist, you will specialize in creating and enhancing machine learning technologies in areas such as Natural Language Processing (NLP) , Computer Vision(CV), and large language models(LLM). You will be a key player within a dynamic team, contributing to and collaborating with other talented colleagues on cutting-edge machine learning challenges from a real ads recommender system. 

In this role you will have the opportunity to solve for problems related to Ads selection and Ads ranking.

Computational Advertising has emerged as a new interdisciplinary field encompassing information retrieval, machine learning, data mining, statistics, operations research, and micro-economics, to address the complex problems inherent in online advertising. The exponential growth of online advertising offers immense opportunities. At Microsoft, we are constantly challenging ourselves, infusing curiosity and imagination to reshape the realm of possibilities. We innovate in machine intelligence, data analytics, big data, and distributed systems, creating the future with a customer-focused mindset.

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 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 Computer Science, Electrical or Computer Engineering, or related field AND 3+ years related experience (e.g., statistics, predictive analytics, research) 
• OR Doctorate in Computer Science, Electrical or Computer Engineering, or related field AND 1+ year(s) related experience (e.g., statistics, predictive analytics, research) 
• OR equivalent experience 

Preferred Qualifications: 

• PhD with research experience in data science, machine learning and/or related fields.
• Experience developing end to end analytics solutions or ML systems for real world applications.
• Have publications at peer-reviewed Data Science/AI conferences (e.g. KDD- Knowledge Discovery and Data Mining, CIKM- Conference on Information and Knowledge Management, SIGIR- Special Interest Group on Information Retrieval, NeurIPS- Neural Information Processing Systems, CVPR- Computer Vision and Pattern Recognition, ICML International Conference on Machine Learning, ICLR- International Conference on Learning Representations, ICCV- International Conference on Computer Vision, and ACL- Association for Computational Linguistics). 

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 and processes offers for these roles on an ongoing basis.

#MicrosoftAds# #Advertising#  #MachineLearning# #LLM #MicrosoftAI

• Participate in design, implementation, and execution across a variety of features regarding data science and machine learning. 
• Drive innovations in analytics applications, retrieval, ranking and generic Natural Language Processing (NLP), Computer Vision (CV) models used in an ads recommender systems. 

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