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Title: Data Scientist, Basketball Data Strategy

Department: Basketball Data Strategy, Basketball Operations

Reports to: Senior Data Scientist, Basketball Data Strategy

Manages: None

Position Summary: The Data Scientist, Basketball Data Strategy is a critical member of the Basketball Data Strategy team. Reporting to the Senior Data Scientist, Basketball Data Strategy, they will develop, test, and maintain predictive models and metrics for player evaluation, roster construction, player development, and in-game strategy. They will work with the Development team to create data visualizations and applications to assist in the consumption of results, and with the Data Engineering team to perform crucial data maintenance and upkeep of models and metrics. The Data Scientist will primarily work under the direction of the Senior Data Scientist and collaborate with other members of the Basketball Data Strategy team to provide tools needed for team success.

Essential Functions (Duties & Responsibilities**):

Utilize statistical analysis, machine learning, and predictive modeling techniques to provide solutions for Basketball Operations
Drive development of production-level models — from exploratory data analysis and problem framing all the way through model validation and deployment
Integrate novel research, basketball metrics, and models into existing and new applications
Originate innovative ways to analyze / summarize data from existing and new stakeholders (e.g. G League, Player Health, NBA Draft)
Operate in both the ad-hoc and the long-term, creating new research and sustainable solutions as necessary in collaboration with the rest of the Basketball Operations department
Manipulate and leverage large data for analysis and modeling; source, process, and understand new datasets that may aid in potential evaluations
Translate data-driven results into actionable basketball decisions and recommendations

Education

Bachelor’s in Statistics, Computer Science, or a related field, or equivalent academic or professional experience

Minimum Qualifications

3+ years of professional experience in a data science or machine learning role
Proficiency in Python or equivalent language for end-to-end model development
Experience using modern machine learning and deep learning techniques (e.g. scikit-learn, TensorFlow) to build robust models
Expertise with techniques to analyze and use large data sets (e.g. PySpark, SQL); willingness to work with geolocation tracking data and biomechanical data
Familiarity with distributed computing and cloud-first principles
Ability to write clean and efficient code; proficiency with version control and code modularization
Strong communication skills
Experience with time series/probabilistic forecasting, MLOps and GPU computing is a plus

Other Qualifications

Adaptable, eager to self-learn new technical skills
Knowledge of and passion for NBA basketball

Location: El Segundo (office M‐F), and other occasional off‐site events

Travel: Less than 5% of the time

Hours: Full-time. Must be available to work evenings, weekends, and holidays as reasonably required

The pay range for this role is $150,000 - $160,000 annually. Actual compensation packages are based on several factors that are unique to each candidate, including but not limited to skill set, depth of experience and certifications. In addition to those factors, we consider the relative pay of our current employees in similar positions when making a final offer.

We are an equal opportunity employer and all qualified applicants will receive consideration for employment without regard to race, color, religion, national origin, sex, sexual orientation, age, disability, gender identity, marital or veteran status, or any other protected class.

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