Data Scientist - Digital : Job Details

BSE Global (“BSE”) is a multifaceted sports and entertainment business that brings people together to experience music, sports, and culture through our teams and venues. We aim to elevate our business, grow our fan base, and cultivate a community rooted in belonging and inclusion, both on and off the court.

SUMMARY

As a Data Scientist, you will lead high-impact analytics projects—such as Bayesian engagement scoring, purchase-propensity, and lifetime-value models—and drive marketing analytics efforts including campaign attribution and ROI measurement. You will collaborate with cross-functional teams to convert complex data into actionable insights, develop predictive and prescriptive models, and influence our data-driven strategies for fan acquisition, retention, and revenue growth.

WHAT YOU WILL DO :

• Lead development of machine-learning solutions (forecasting, classification, recommendation, clustering) using Python and libraries like scikit-learn, XGBoost, TensorFlow, or PyTorch.
• Deploy models in cloud environments (Snowflake, Dataiku, or custom pipelines), ensuring scalability and performance.
• Follow and improve BSE's MLOps processes—evaluating effectiveness, identifying gaps, and collaborating with engineering teams for deployment, monitoring, and governance.
• Assist in designing and deploying AI-powered solutions, including intelligent agents and LLM-integrated applications, using platforms such as Amazon Bedrock and Snowflake Cortex.
• Create user-friendly data products with intuitive design and engaging visuals to promote adoption among technical and non-technical stakeholders.
• Work with data engineers to source, clean, and blend structured and unstructured data from data lakes and warehouses (Snowflake, S3, Postgres).
• Engineer features to enhance model accuracy and interpretability, including temporal, behavioral, and spatial features.
• Design and execute A/B tests, uplift modeling, and causal inference analyses to evaluate marketing campaigns and in-venue experiences.
• Develop customer segmentation and lifetime-value models to inform personalization and loyalty initiatives.
• Collaborate with teams across ticketing, marketing, finance, and IT to translate business questions into analytical solutions.
• Present findings clearly and effectively, translating model results into actionable business insights.
• Promote best practices in reproducible research—version control, code reviews, testing, and documentation.
• Mentor junior analysts, fostering a culture of learning and experimentation.
• Create impactful visualizations and dashboards using tools like Tableau or Looker to communicate insights and align stakeholders.

WHAT YOU WILL BRING :

• Bachelor's degree in Data Science, Statistics, Computer Science, Engineering, Marketing Analytics, or related field; Master's or PhD preferred.
• At least 3 years of practical experience in data science or analytics, with hands-on work on Bayesian and predictive models and marketing analytics solutions.
• Experience deploying models in cloud platforms (AWS, GCP, Azure) and integrating with modern data stacks (Snowflake, Databricks, Dataiku).
• Strong knowledge of digital marketing metrics (CTR, CPA, ROAS) and familiarity with analytics tools like Google Analytics and Adobe Analytics.
• Experience in data modeling and supporting analytics/reporting, with tools such as dbt or coalesce preferred.
• Ability to document workflows clearly and share knowledge effectively within teams.
• Excellent communication skills, capable of presenting complex data insights to diverse audiences.

WHO YOU ARE :

• Proficient in Python and data manipulation techniques, with a solid understanding of data warehousing concepts.
• Detail-oriented and capable of working accurately with large datasets.

TRAVEL REQUIREMENTS :

Travel may be required occasionally.

SALARY RANGE : $85,000 - $110,000

WORK ENVIRONMENT :

Primarily in an office setting.

We are an Equal Employment Opportunity (“EEO”) Employer. We do not discriminate based on race, color, religion, gender, gender identity, sexual orientation, age, national origin, disability, veteran status, or other protected characteristics.