Data ScientistSan Francisco, California Requisition Number R0019080 Subsidiary StubHub
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ORGANIZATION: StubHub,www.stubhub.com (an eBay company NASDAQ: EBAY)
StubHub’s purpose is to connect people through inspiring event experiences. We connect fans with their favorite teams, shows and artists and introduce them to the ones they'll love next. As the largest ticket marketplace in the world, we enable fans to buy and sell tickets to tens of thousands of events, whenever they want, through our desktop and mobile experiences, including our StubHub app for iPhone, iPad, Apple Watch and Android. Offering a superior fan experience at its core, StubHub reinvented the ticket resale market in 2000 and continues to lead it through innovation. Our industry firsts include the introduction of the first ticketing application, the first interactive seat mapping tool and the first live entertainment rewards program, Fan Rewards™. Our business partners include more than 130 properties in MLB, NBA, NHL, MLS and NCAA, plus AEG, AXS and Spectra Ticketing & Fan Engagement. With the acquisition of Ticketbis in August 2016, throughout the world, StubHub provides the total end-to-end event going experience. StubHub is an eBay company (NASDAQ: EBAY). For more information on StubHub, visit StubHub.com or follow @StubHub on Twitter, Facebook and Instagram or YouTube.com/StubHub.
In this role, you will be responsible for developing proprietary machine learning models that improve user experience and drive StubHub business. You will work closely with the product and technology teams to deploy your algorithms in production with high fidelity.
The role is based in StubHub’s San Francisco headquarters. It reports to the Senior Data Science Manager and sits side by side with our integrated data science, data engineering and analytics functions.
Apply the state of the art machine learning algorithms to enhance the user experience.
Drive feature engineering and experimentation to improve model performance with a large set of proprietary data on users, performers, sports teams and events.
Actively participate in the discussion of product roadmap, data science initiatives and the optimal approach to apply the underlying algorithms.
Collaborate with other members in data science and analytics on data mining and predictive modeling.
PhD in machine learning, computer science, operations research or an equivalent quantitative field, or Master with relevant industrial experience.
Ability to translate a complex business or social problem into an actionable and testable model.
Excellent software development skills. Proficiency with data science tools like Python, R, relational database, and Hadoop/Spark.
Passion about sports and the live entertainment industry is strongly preferred.
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