City : Vancouver

Category : See Posting

Industry : Technology

Employer : Microsoft

Our team focuses on understanding, predicting, and incentivizing how the advertisers and users interact with our marketplace through algorithm development, optimization, and experimental analysis of advertiser strategies and auction mechanisms. In our team, engineers and scientists work together and utilize all sorts of platforms, techniques, and approaches, including but not limited to game theory, economics, machine learning, optimal control, mathematical modeling, and optimization. We build and develop both online stack as well as offline workflows. At its core, our team utilizes signals of user and advertiser intent to determine in real-time or near-real-time which ads can enter the auctions, how they are allocated, and the price they get charged. Our works directly impact billions of dollars in revenue annually.

Responsibilities

We are looking for a highly skilled data & applied scientist with development skills and a strong background in quantitative fields such statistical machine learning, microeconomics, decision theory, operation research, optimization theory, mathematical modeling, data mining, causal inference, information retrieval, game theory, mechanism design, optimal control, or related fields. They will play a key role in driving algorithmic improvements to online and offline systems, developing and delivering robust and scalable solutions, making direct impacts on both users' and advertisers' experience, and continually increasing the revenue for Bing Ads.

Responsibilities include:

• Making algorithmic improvements to the Bing Ads auction mechanism using principles of game theory.
• Designing, implementing, and analyzing bidding strategies using techniques from optimization, control theory.
• Designing, implementing, and deploying large-scale optimization algorithms to manage the Bing Ads' marketplace.
• 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 advertisers’ return on investment.

Developing models for causal reasoning using techniques from AI, ML, and statistics.

Qualifications

Required Qualifications:

• 2 years of experience, either in academic research settings or industry, 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.
• 2 years of development experience (can be overlapped with the quantitative experience above)

   

  Preferred Qualifications:

• Research experience (publications) in the following areas is preferred statistical machine learning, deep learning, data mining, causal inference, information retrieval, game theory, mechanism design, optimization, and optimal control

• Experience with computational advertising
• A graduate degree in CS/EE or related quantitative field.

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.

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