Microsoft
Principal Applied Scientist
Microsoft, Mountain View, California, us, 94039
We are looking for skilled
Principal Applied Scientist
with background in Machine Learning, Reinforcement Learning, Causal Inference, Large Language models, Natural Language Processing (NLP)/Natural Language Generation (NLG) techniques, Control Theory, Data Science, Data Mining, or related fields.
This role is located in either
Mountain View, CA
or
Redmond, WA .
Candidates should have a keen interest in artificial intelligence and optimization at web scale. They will play a key role in driving algorithmic improvements to online and offline systems, develop and deliver robust and scalable solutions, make direct impact to both user and advertisers experience, and continually increase the revenue for Bing ads.
Our team focuses on selecting relevant ads and modeling how users interact with ad content on a search engine. Generating and understanding ad content and predicting how the user interacts with the ads on the search results page, or conversational interfaces, are critical modeling tasks. The probability that a user will click on an ad or interact with the advertiser’s landing page after clicking are important for measuring advertiser and user satisfaction. This position is for the Signals modeling team, which builds machine learned models for predicting such events. Matching to advertiser provided content and also dynamically creating informative ad content to address user’s information needs are also important modeling aspects of our team.
The team looks at all aspects of modeling including training data, features, the actual model (Large Language Models, neural nets, linear models, Gradient Boost Decision Tree(GBDT) etc.) and offline and online evaluation of those models. Engineers and scientists on our team work at the edge of machine learning and economics developing in the online stack as well as offline workflows. At its core, our team utilizes signals of user and advertiser intent to determine which ads are allocated and at what price.
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. In alignment with our Microsoft values, we are committed to cultivating an inclusive work environment for all employees to positively impact our culture every day.
Responsibilities
Designing and building efficient models for predicting user interactions with ads and advertiser’s pages.
Designing and overseeing large-scale, long-term experiments to improve the health of the marketplace using advanced statistics and machine learning.
Designing automation algorithms for advertisers using techniques from AI and ML to improve advertiser’s return on investment.
Develop models for causal reasoning using techniques from AI, ML, and statistics.
QualificationsRequired/Minimum Qualifications:
Bachelor's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 8+ 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 6+ years related experience (e.g., statistics, predictive analytics, research)
OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 5+ years related experience (e.g., statistics, predictive analytics, research)
OR equivalent experience
7+ years of experience in Research or Data Science role.
Preferred Qualifications:
Research experience (publications) in the following areas is preferred: statistical machine learning, deep learning, data mining, causal inference, information retrieval, and Bayesian inference.
Expertise and practical experience in using statistical machine learning, deep learning, data mining, information retrieval, optimization and Bayesian inference.
Enhanced problem solving and data analysis skills.
Effective communication skills, both verbal and written.
Applied Sciences IC6 - The typical base pay range for this role across the U.S. is USD $158,500 - $276,600 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 $202,800 - $304,200 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 will accept applications for the role until September 14, 2024.
Microsoft is an equal opportunity employer. Consistent with applicable law, all qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship, color, family or medical care leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable local laws, regulations and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application process, read more about requesting accommodations.
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Principal Applied Scientist
with background in Machine Learning, Reinforcement Learning, Causal Inference, Large Language models, Natural Language Processing (NLP)/Natural Language Generation (NLG) techniques, Control Theory, Data Science, Data Mining, or related fields.
This role is located in either
Mountain View, CA
or
Redmond, WA .
Candidates should have a keen interest in artificial intelligence and optimization at web scale. They will play a key role in driving algorithmic improvements to online and offline systems, develop and deliver robust and scalable solutions, make direct impact to both user and advertisers experience, and continually increase the revenue for Bing ads.
Our team focuses on selecting relevant ads and modeling how users interact with ad content on a search engine. Generating and understanding ad content and predicting how the user interacts with the ads on the search results page, or conversational interfaces, are critical modeling tasks. The probability that a user will click on an ad or interact with the advertiser’s landing page after clicking are important for measuring advertiser and user satisfaction. This position is for the Signals modeling team, which builds machine learned models for predicting such events. Matching to advertiser provided content and also dynamically creating informative ad content to address user’s information needs are also important modeling aspects of our team.
The team looks at all aspects of modeling including training data, features, the actual model (Large Language Models, neural nets, linear models, Gradient Boost Decision Tree(GBDT) etc.) and offline and online evaluation of those models. Engineers and scientists on our team work at the edge of machine learning and economics developing in the online stack as well as offline workflows. At its core, our team utilizes signals of user and advertiser intent to determine which ads are allocated and at what price.
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. In alignment with our Microsoft values, we are committed to cultivating an inclusive work environment for all employees to positively impact our culture every day.
Responsibilities
Designing and building efficient models for predicting user interactions with ads and advertiser’s pages.
Designing and overseeing large-scale, long-term experiments to improve the health of the marketplace using advanced statistics and machine learning.
Designing automation algorithms for advertisers using techniques from AI and ML to improve advertiser’s return on investment.
Develop models for causal reasoning using techniques from AI, ML, and statistics.
QualificationsRequired/Minimum Qualifications:
Bachelor's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 8+ 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 6+ years related experience (e.g., statistics, predictive analytics, research)
OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 5+ years related experience (e.g., statistics, predictive analytics, research)
OR equivalent experience
7+ years of experience in Research or Data Science role.
Preferred Qualifications:
Research experience (publications) in the following areas is preferred: statistical machine learning, deep learning, data mining, causal inference, information retrieval, and Bayesian inference.
Expertise and practical experience in using statistical machine learning, deep learning, data mining, information retrieval, optimization and Bayesian inference.
Enhanced problem solving and data analysis skills.
Effective communication skills, both verbal and written.
Applied Sciences IC6 - The typical base pay range for this role across the U.S. is USD $158,500 - $276,600 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 $202,800 - $304,200 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 will accept applications for the role until September 14, 2024.
Microsoft is an equal opportunity employer. Consistent with applicable law, all qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship, color, family or medical care leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable local laws, regulations and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application process, read more about requesting accommodations.
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