Senior Data Scientist

Brooklyn Sports & Entertainment (BSE) creates bold, authentic, and unforgettable experiences that redefine sports, entertainment, and hospitality, The Brooklyn Way. As the parent company of marquee properties including the Brooklyn Nets, NY Liberty and Barclays Center, BSE operates at the intersection of live entertainment, premium hospitality, and community engagement.   

As it expands its existing portfolio, BSE now includes a media portfolio including Type.Set.Brooklyn and BK Mag, as well as Brooklyn Wine Club, and a hospitality business developing several location-based entertainment properties.   

Whether on the court, on stage, or in the workplace, BSE is driven by a pursuit of excellence—constantly evolving, innovating, and pushing boundaries to elevate its business and expand its fan base. The company is deeply committed to fostering a culture of belonging and inclusion, both internally and across its communities, ensuring that every interaction reflects its values of growth mindset, integrity, accountability and care.  

We are guided by our core values: 

• Integrity: Be intellectually honest at all times. Demonstrate the highest professional and ethical standards.
• Care: Care for everything and everyone around us. Practice empathy, respect, and inclusion to promote an environment of excellence and success.
• Growth Mindset: Develop ourselves and those around us. Experiment, learn, and improve from everything we do.
• Accountability: Deliver on our word, take responsibility for our actions, and work in the interest of our team. .

SUMMARY

As a Senior Data Scientist, you will own high-impact analytics projects—ranging from Bayesian engagement scoring to purchase-propensity and lifetime-value models—and drive our marketing analytics efforts, including campaign attribution and ROI measurement. You’ll partner with cross-functional stakeholders to build out our data science function, data science standard operating procedures, and action on our vison for how predictive analytics shape the future of BSE. You’ll turn complex data into actionable insights, build and deploy predictive and prescriptive models, and help shape our data-driven strategy for fan acquisition, retention, and revenue growth.

WHAT YOU WILL DO

• Lead end-to-end development of machine-learning solutions (forecasting, classification, recommendation, clustering) using Python and popular libraries (scikit-learn, XGBoost, TensorFlow/PyTorch).
• Productionize models in cloud environments (Snowflake, Dataiku, or custom ML pipelines), ensuring scalability, performance, and monitoring.
• Champion and adhere to BSE’s established ML Ops process—regularly evaluate its effectiveness, identify gaps, and collaborate with engineering and operations teams to enhance model deployment, monitoring, and governance.
• Think critically about the business problem at hand and deploy the appropriate measurement technique
• Assist w/ design, development, and deployment of AI-powered solutions—including intelligent agents and LLM-integrated applications—using platforms like Amazon Bedrock, Snowflake Cortex, and other generative AI technologies.
• Design and execute A/B tests, uplift modeling, and causal inference analyses to quantify the impact of marketing campaigns, pricing initiatives, and in-venue experiences.
• Develop customer segmentation and lifetime-value frameworks to inform personalization and loyalty programs.
• Partner closely with ticketing, merchandising, marketing, finance, and IT teams to translate business questions into analytical solutions.
• Evangelize best practices for reproducible research: version control (Git), code reviews, unit testing, and documentation.
• Mentor junior data analysts, fostering continuous learning and promoting a culture of experimentation.

WHAT YOU WILL BRING

• Bachelor’s degree in Data Science, Statistics, Computer Science, Engineering, Marketing Analytics, or related quantitative field—or equivalent practical experience. Masters or PhD preferred.
• 8+ years work experience using analytics and/or data science to solve problems, with hands-on experience in a wide range of measurement and prediction techniques (Bayesian modeling, correlation analysis, observational causal inference, ranking/recommendation, and/or time-series/forecasting).
• Hands-on depth with Python, SQL/PySpark, ML frameworks (scikit-learn/XGBoost/TensorFlow/PyTorch), and MLOps (feature stores, MLflow/model registry, CI/CD, online serving)
• Cloud platform expertise (AWS preferred), containers/Kubernetes, and integrating with modern data stacks (Snowflake, Databricks, Dataiku).
• Strong understanding of digital-marketing metrics (CTR, CPA, ROAS) and analytics tools (Google Analytics, Adobe Analytics).
• Ability to document workflows clearly and contribute to knowledge sharing within the team.

WHO YOU ARE

• Experienced solo data scientist or experience leading a team of data scientists preferred.
• Effective technical communicator who can convey clear recommendations to a variety of audiences (Technology, Marketing, senior leadership).
• Excellent written and verbal communication skills, with the ability to effectively present complex data and insights to both technical and non-technical stakeholders.
• Strong attention to detail and the ability to work with large datasets accurately and efficiently.

COMPENSATION

$100,000 - $150,000

Full-time employees are eligible for a robust slate of total rewards, including:

• Bonus eligibility
• Medical, dental, and vision coverage; HSA and FSA eligibility
• 401k Employer Match at 4%
• Competitive PTO policy & Company Holidays
• Parental leave policy eligible after 6 months of service
• Access to events at Barclays Center, subject to ticket availability
• Free lunch onsite Monday - Thursday; onsite barista bar
• And more!

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/creed, gender, gender identity, transgender status, pregnancy and lactation accommodations, marital status, partnership status, domestic violence victim status, sexual orientation, age, national origin, alienage, immigration, or citizenship status, veteran or military status, disability, genetic information, height and weight, arrest or conviction record, caregiver status, credit history, unemployment status, sexual and reproductive health decisions, salary history, status as a victim of domestic violence, stalking, and sex offenses, or any other characteristic prohibited by federal, state or local laws.