BSE is looking to expand its data science function and leverage predictive analytics to shape the future of fan acquisition, retention, and revenue growth.
Requirements
- 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).
- 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).
- Ability to document workflows clearly and contribute to knowledge sharing within the team.
- Bachelor’s degree in Data Science, Statistics, Computer Science, Engineering, Marketing Analytics, or related quantitative field—or equivalent practical experience.
- Masters or PhD preferred.
Responsibilities
- 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.
Other
- 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.
- 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).
