Microsoft is a company dedicated to empowering individuals and organizations globally. The Applied Scientist II role focuses on modeling user interactions with ads, utilizing machine learning techniques to build predictive models and improve marketplace health through advanced statistics and experimentation.
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
Skills
- 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
- 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
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