Detroit Pistons-posted 11 days ago
Full-time • Entry Level
Detroit, MI

Are you looking to joining a team of go-getters dedicated to serving and uplifting the community through basketball? Join the Detroit Pistons team and our mission to empower! The Pricing Analyst will focus on optimizing ticket pricing strategies and building predictive models to understand fan purchasing behavior. This role combines advanced analytics, statistical modeling, and business insight to deliver actionable recommendations that drive revenue growth and improve fan engagement. The analyst will work closely with ticketing, marketing, and finance teams to ensure models are accurate, understood, and effectively implemented. We are seeking a team member with a positive, upbeat attitude that can connect with a diverse population, and we are excited to meet you!

  • Model Development & Analysis
  • Build and deploy predictive models for ticket pricing and propensity to purchase.
  • Back-test models and compare performance to ensure accuracy and reliability.
  • Balance “business significance” vs. “statistical significance” to drive practical adoption.
  • Data Preparation & Reporting
  • Standardize and prepare data for modeling and analysis.
  • Translate complex statistical concepts into clear, business-friendly presentations.
  • Deliver ad-hoc reporting and analysis to support ticketing and marketing initiatives.
  • Pricing & Inventory Management
  • Dynamically price single-game ticket inventory across all products.
  • Manage ticket inventory to maximize revenue and fan accessibility.
  • Stakeholder Collaboration
  • Work with internal stakeholders to ensure models are understood and implemented properly.
  • Communicate insights effectively to technical and non-technical audiences.
  • Bachelor’s degree in Data Science, Statistics, Mathematics, or related field.
  • 2–4 years of experience in data analytics, predictive modeling, or revenue management preferred.
  • Experience with machine learning techniques and statistical modeling.
  • Proficiency in SQL and either Python or R (familiarity with all is a plus).
  • Familiarity with BI tools (Tableau, Power BI) and data visualization best practices.
  • Experience in sports or live events preferred (willing to trade some technical depth for industry experience).
  • Solid understanding of statistical modeling concepts and predictive analytics.
  • Intellectual curiosity and a proactive approach to posing new questions and finding answers.
  • Ability to balance technical rigor with business impact and user adoption.
  • Strong analytical, problem-solving, and communication skills.
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