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This role is part of the Microsoft Search & Ads Network (MSAN) modeling team, focused on building large-scale machine learning systems for ads retrieval, ranking, and marketplace optimization across different surfaces. The team develops end-to-end models that predict user engagement and advertiser value—powering candidate generation, relevance scoring, and serving stack ranking that directly impact ad quality, delivery efficiency, and revenue. Responsibilities span the full modeling lifecycle, including training data and labeling strategy, feature and signal design, model development, and rigorous offline and online evaluation. Engineers and applied scientists work closely at the intersection of machine learning, economics, and large-scale systems to deliver high-performance real-time inference and robust experimentation in production.
Job Responsibility:
Have a solid background in Machine Learning, Reinforcement Learning, Causal Inference, Data Science, Data Mining, or related field
Be passionate about artificial intelligence and optimization at web scale
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
Requirements:
Bachelor'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 Master's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 3+ years related experience (e.g., statistics, predictive analytics, research)
OR Doctorate 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 equivalent experience
Nice to have:
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 3+ years related experience (e.g., statistics, predictive analytics, research)
OR equivalent experience
Research experience (publications) in the following areas: statistical machine learning, deep learning, data mining, causal inference, information retrieval, and Bayesian inference
2+ years of 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
Proficient problem solving and data analysis skills
Proficient software design and development skills/experience