Data Science Lead
Posted on Nov 19, 2018 by National Basketball Association
As a global sports and media business, the NBA is so much more. While Basketball Operations runs the league's on-court activities, other departments manage relationships with television and digital media partners, develop marketing partnerships with some of the world's most recognizable companies, oversee the licensing of NBA merchandise, and handle a wide range of responsibilities that drive the NBA's success.
The National Basketball Association is seeking an experienced, hands-on data science leader to join the Analytics and Data Science team in Customer Data Strategy (CDS) in New York. He/she will focus on elevating the NBA's use of analytics, predictive modeling and data visualization to take the league and our teams and partners to the next level with our vision of 'deepening engagement with fans, both prospective and existing, that builds a lifetime love of the game'. The role involves leveraging current varied data streams and corralling new ones to inform a single view of the fan across the NBA's global touchpoints, including both on and offline platforms and channels.
S/he will have 10 or more years of practical experience in the analytics space including 2 or more years of people leadership. The candidate will lead a team of data scientists in a variety of advanced analytics projects and is charged with the task of creating and managing a suite of predictive models (e.g. propensity models, topic models, subscriber churn models, estimations of fan value, marketing mix and attribution models) that enables the NBA, our teams and our partners to establish greater engagement with our fans.
The role reports to AVP, Analytics and Data Science within CDS.
- Lead advanced analytic projects that solve complex business problems for the NBA, teams and partners
- Partner with leadership to define, prioritize and execute use cases that drive measurable lift to fan engagement, revenue and partner value
- Manage and enhance inventory of existing propensity and segmentation models to help the league, teams and partners deliver to revenue growth objectives
- Create new predictive models to grow fan engagement for the league, teams and partners
- Responsible for managing 2 members of the data science team; Mentors and provides thought leadership throughout the league and team analytics community
- Prepares presentations that clearly communicate project findings to business partners
- The candidate must have a sufficient understanding of and practical experience with machine learning algorithms (e.g. gradient boosting, neural networks) as well as classic statistical modeling techniques (e.g. logistic regression, CART, K-means clustering)
- Comfort with ambiguous and large streams of data across different formats and entry points; Hands-on experience working with large data processing; familiarity with applications like Hadoop, Spark, AWS
- Strong knowledge of Python, R and SQL required
- Excellent communication and writing skills to explain complex outcomes to business partners that may not have extensive quantitative backgrounds
- Ability to work within tight deadlines and changing priorities
- A minimum of 10 years of practical business intelligence and data science experience, preferably in the entertainment or ad tech industries
- Experience working with ad tech and digital clickstream analytics tools such and Adobe Analytics or Google Analytics
- Exemplary data visualization skills. Experience with Tableau a plus
- Expert-level SQL and R coding
Educational Background Required:
- Ph. D or master's degree in statistics, mathematics, operations research, economics or related quantitative field.
We Consider Applicants For All Positions On The Basis Of Merit, Qualifications And Business Needs, And Without Regard To Race, Color, National Origin, Religion, Sex, Gender Identity, Age, Disability, Alienage Or Citizenship Status, Ancestry, Marital Status, Creed, Genetic Predisposition Or Carrier Status, Sexual Orientation, Veteran Status, Familial Status, Status As A Victim Of Domestic Violence Or Any Other Status Or Characteristic Protected By Applicable Federal, State, Or Local Law.
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