Principal Applied Scientist

Microsoft Audience Network (MSAN) part of the Web Experiences Team (WebXt) is seeking a Principal Applied Scientist to join us in 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 Principal 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.

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.

Our Culture: Microsoft Culture

Our Team: Inside Microsoft's Web Experiences Team

Qualifications:

Required qualifications:

• Bachelor's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 6+ 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 4+ years related experience (e.g., statistics, predictive analytics, research)
  • OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 3+ years 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, CIKM, SIGIR, NeurIPS, CVPR, ICML, ICLR, ICCV, and ACL)

Applied Sciences IC5 - The typical base pay range for this role across the U.S. is USD $133,600 - $256,800 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 $173,200 - $282,200 per year.

Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here: https://careers.microsoft.com/us/en/us-corporate-pay

Microsoft is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, ancestry, color, family or medical care leave, gender identity or expression, genetic information, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran status, race, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable laws, regulations and ordinances. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. If you need assistance and/or a reasonable accommodation due to a disability during the application or the recruiting process, please send a request via the Accommodation request form .

Benefits/perks listed below may vary depending on the nature of your employment with Microsoft and the country where you work.

Responsibilities:

• 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 NLP, CV models used in an ads recommender systems