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

As a 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 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.
• 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.
• Build user-centric data products with thoughtful design and seamless user experience in mind. Ensure tools are intuitive, visually engaging, and inspire adoption across non-technical and technical stakeholders.
• Source, wrangle, and blend structured and unstructured data from the data lake/warehouse (Snowflake, S3, Postgres) in collaboration with data engineers.
• Engineer robust features—temporal, behavioral, spatial—to drive model accuracy and interpretability.
• 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.
• Distill model findings down to tangible business recommendations and insights to drive adoption
• 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.
• Create clear, impactful visualizations and narratives—using tools such as Tableau, Looker, or custom dashboards—to translate complex model outputs into actionable insights and drive stakeholder alignment.

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.
• 3+ years in applied data science or analytics, with hands-on experience building Bayesian and predictive models and marketing-analytics solutions (attribution, campaign analysis).
• Experience deploying models in cloud environments (AWS, GCP, or Azure) 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).
• Familiarity with data modeling principles and experience building data models to support analytics and reporting. Use of data modeling tools such as dbt and/or coalesce preferred.
• Ability to document workflows clearly and contribute to knowledge sharing within the team.
• Excellent written and verbal communication skills, with the ability to effectively present complex data and insights to both technical and non-technical stakeholders.

WHO YOU ARE:

• Proficient in python and data wrangling techniques, with a strong understanding of data manipulation, data warehousing concepts and structures.
• Detail-oriented with the ability to work with large datasets accurately and efficiently.

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:

$85,000 - $110,000

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.