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Research Scientist


Headquarters: Sunnyvale, CA
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Oath Ad Platforms is our unified ad tech solution for both advertisers and publishers. Our innovative ad tech gives one stop access to Oath's trusted data, high quality inventory and demand, creative ad experiences and industry-leading machine learning, at global scale.

The Demand Platforms R&D team at Oath Inc. in Sunnyvale, California, is the core group within Oath Inc. (fully owned subsidiary of Verizon) to solve complex and crucial problems for Oath’s demand side business: optimally buying in real time digital advertising opportunities on behalf of advertisers. The team makes use of advanced techniques from the literature, but mostly develops and patents ground-breaking new methodologies in-house. The research team is composed of scientists with backgrounds from diverse fields such as electrical and mechanical engineering, applied mathematics, statistics, neuroscience, operations research, and computer science among others; all of them have at least one thing in common: they are passionate and love problem solving. We are looking for a exceptionally strong and experienced researcher to join the R&D team to work on estimation algorithms for the value of showing an ad, typically implying the prediction of events like a click on the ad and/or a subsequent action by the user. In addition, the researcher could also work on related research problems critical for the company to stay relevant in the business of programmatic advertising. 

The work involves algorithm development, implementation, online testing with real campaigns, and ultimately supervising performance in production. It is a great opportunity for an ambitious and passionate Ph.D. level scientist with a few years of experience and background in system engineering, computer science, operations research, statistics, electrical engineering, statistical learning or related fields, to apply such experience to improve the performance of Oath’s programmatic ad bidding systems, and consequently its business bottom line. 


  • Design and apply state of the art machine learning algorithms to predict very rare events based on very large and high dimensional data sets from online advertising systems.
  • Perform statistical analysis of massive amounts of Internet data
  • Propose, validate, and implement estimation and prediction algorithms to optimize bidding on online impression opportunities
  • Gather requirements, propose solutions, create roadmaps and plans.
  • Collaborate with multiple teams spanning R&D, engineering, product, and business strategy.
  • Design experiments to test and validate the control algorithms
  • Present all findings in reports and presentations 


  • Ph.D. in computer science, statistics, operations research, electrical or mechanical engineering, or a similar field with at least 2 years of experience from industry or equivalent.
  • Solid background in statistical theory and analysis, as well as machine/statistical learning.
  • Hands-on programming skills in java or C++ is required, and experience with shell scripts and script languages such as Python, MATLAB, R, and SQL is nice to have
  • Experience working with massive data sets, e.g. using Hadoop, Spark, Scala, Tensorflow, etc
  • A very hands-on attitude, willing to do what it takes to get things done, beyond the comfort zone.
  • Outstanding team spirit with excellent communication and writing skills
  • Hard-working and with a desire and habit to go above and beyond
  • Exceptionally high integrity and highly detail oriented 
Oath is proud to be an equal opportunity workplace. All qualified applicants will receive consideration for employment without regard to, and will not be discriminated against based on, age, race, gender, color, religion, national origin, sexual orientation, gender identity, veteran status, disability or any other protected category. Oath is dedicated to providing an accessible environment for all candidates during the application process and for employees during their employment. Please let us know if you need a reasonable accommodation to apply for a job or participate in the application process.