Applied Scientist II

Microsoft • Redmond, WA

63d

About The Position

Our team focuses on understanding and predicting how the user interacts with the ads on the search results page. The probability that a user will click on an ad is one of the most critical inputs used in ranking the ads. Similarly, the probability of interacting with the advertiser’s page is important for measuring advertiser and user satisfaction. This position as an Applied Scientist II is for the modeling team, which builds machine learned models for predicting such events. The team looks at all aspects of modeling including training data, features, the actual model (neural nets, linear models, decision trees 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.

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.

Nice To Haves

• 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
• Experience in any of the following areas statistical machine learning, deep learning, data mining, causal inference, information retrieval, game theory, mechanism design, optimization and Bayesian inference.
• Excellent problem solving and data analysis skills, effective communication skills, both verbal and written.
• Solid software design and development skills/experience.
• 1+ year(s) experience creating publications (e.g., patents, peer-reviewed academic papers).
• Research experience (publications) in the following areas is preferred statistical machine learning, deep learning, data mining, causal inference, information retrieval, and Bayesian inference.

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.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Number of Employees: 5,001-10,000 employees