BSE Global (“BSE”) is a multifaceted sports and entertainment business that brings people together to experience music, sports, and culture through our teams and venue. Through these experiences and in our workplace, we strive to elevate our business, grow our fan base, and cultivate a community anchored in belonging and inclusion in every aspect, on and off the court.

SUMMARY

We’re looking for a Data Scientist that will be responsible for assisting with building strategy and implementing of sophisticated analytical models, including predictive, prescriptive, artificial intelligence, and machine learning. You will help the data science team lead efforts related to the business of the Brooklyn Nets, New York Liberty, Long Island Nets and Barclays Center and all other BSE Global properties.

The Data Scientist will aid and assist with implementing standard processes for data and machine learning methodologies for the company, using data to forecast and influence business decisions. This role will serve as a valued cross-functional contributor, engaging with a range of collaborators across highly-technical and strategic topics. The ideal candidate will be a highly motivated self-starter with an unparalleled work ethic and customer-focused mentality.

WHAT YOU WILL DO:

• Develop, iterate, and take to production machine learning models to predict business outcomes, fan behavior, and solve problems.
• Assist with the development and implementation of the company’s data science strategy, including the use of predictive analytics to tell a story, deliver insights and drive strategic growth.
• Build, validate, automate, and own predictive models to elevate and drive business results.
• Help champion standard methodologies in analytics instrumentation and experimentation.
• Work closely with clients to identify patterns and trends in their data and translate these into actionable insights.
• Work with decision-makers across the company to understand their goals, see opportunities to use data to develop new insights and improve business results.
• Collaborate with business intelligence team and cross-functional teams in problem framing and conception of ideas to develop consensus and complete the machine learning use cases.
• Build machine learning models through all phases of development from design, testing, data gathering, training, evaluation, validation, governance, and implementation.
• Maintain the health of machine learning systems, including speed, model accuracy, reliability, and performance.
• Champion efforts to craft and implement strategic fan growth initiatives such as models for : lifetime value forecasting, subscriber lapse propensity, lead scoring, season-ticket member retention, and media mix modeling.
• Measure outcomes and translate analytical insights into recommendations that are clearly linked to the organization's strategy and goals.

WHO YOU ARE:

• A Bachelor’s or Master’s degree in computer science, statistics, data science or relevant analytics field with 2+ years of data science experience.
• Hands-on experience in machine learning, relational databases, and open source programming languages (Python, R) for large scale data analysis.
• Proven track record of delivering business value through analytical models.
• Solid understanding of data science technologies and machine learning concepts and have experience developing models from research, to a proof of concept, to a production pipeline.
• Deep understanding of working in cloud environments, preferably Amazon Web Services.
• Comfortable with command line tools and GitHub
• Excellent communicator with prior experience leading multiple collaborator groups.
• Passion for continuous improvement.

• A cultural leader who can infuse data science and culture of innovation.

TRAVEL REQUIREMENTS:

Travel may be required on rare occasions (< 5% travel); may require air travel and/or overnight stay of one or more nights.

SALARY RANGE:

90000 - 105000

WORK ENVIRONMENT:

Work primarily in an office environment.

We are an Equal Employment Opportunity (“EEO”) Employer. It has been and will continue to be a fundamental policy of the Company not to discriminate on the basis of race, color, creed, religion, gender, gender identity, transgender status, pregnancy, marital status, partnership status, domestic violence victim status, sexual orientation, age, national origin, alienage or citizenship status, veteran or military status, disability, genetic information or any other characteristic prohibited by federal, state or local laws.