Quantitative Data Analyst

The Florida Panthers • Sunrise, FL

15h

About The Position

We are seeking a Quantitative Data Analyst with 1–3 years of experience to transform complex commercial variables into high-fidelity predictive models, replacing anecdotal with mathematically rigorous forecasts. In this role, you will identify hidden yield opportunities across all revenue streams, ensuring every strategic move is backed by an unbiased, forward-looking probability of success. While we value sports or yield management experience, we prioritize a brilliant mathematical mind with elite Python skills; if you bring the technical horsepower, we will provide the industry context and the platform to see your work directly influence a championship organization.

Requirements

• Bachelor’s degree in Mathematics, Statistics, Data Science, or a related quantitative field.
• 1–3 years of experience building and validating predictive and machine learning models.
• Deep understanding of probability, time-series analysis, and statistical significance.
• Proficiency in Python for data analysis and modeling with a focus on writing maintainable, production-ready code
• Proficiency in the full ML lifecycle, including feature engineering, hyperparameter tuning, and cross-validation
• Proven ability to distill complex statistical findings into actionable insights for non-technical stakeholders.

Nice To Haves

• Proficiency in SQL and experience extracting data from cloud warehouses like Amazon Redshift.
• Familiarity with ML Ops concepts, including containerization (Docker) or orchestration (Prefect).
• Experience deploying machine learning models in a real-world, fast-paced commercial environment.
• Experience with price elasticity, dynamic pricing models, or inventory management.
• A passion for sports analytics or experience in the sports and entertainment industry.

Responsibilities

• Build revenue forecasting models and probabilistic simulations using Python to predict performance across all business units.
• Design, train, and validate supervised and unsupervised machine learning models to solve high-impact business problems like Lead Scoring, Customer Lifetime Value (CLV), and Churn Prediction.
• Translate complex statistical outputs into clear, narrative-driven recommendations for executive leadership.
• Write production-grade, modular Python code designed for ML Ops to ensure models are scalable and deployable.
• Analyze price elasticity for tickets and ancillary business lines to drive yield and pricing optimization.
• Monitor and implement emerging machine learning trends to continuously improve predictive accuracy.
• Collaborate with the broader BI team to integrate model outputs into our data environment.

What This Job Offers

• Job Type: Full-time
• Career Level: Entry Level