Lead Data Scientist, Business Strategy & Analytics at Colorado Rockies

Lead Data Scientist, Business Strategy & Analytics ABOUT US The Colorado Rockies Baseball Club is embracing the climb, committed to building a championship-caliber organization on the field, in the clubhouse, and throughout our business operations. Playing at altitude presents unique competitive challenges and opportunities, and we embrace innovation, collaboration, and evidence-based practices to support elite performance. Rooted in the traditions of America’s pastime, we operate with integrity, service, quality, and trust while striving to create an exceptional experience for our players, staff, and fans. The Strategy & Business Analytics team partners closely with leadership and functional departments to translate data into insight, insight into decisions, and decisions into measurable impact. POSITION SUMMARY The Lead Data Scientist will play a foundational role in shaping and executing the Colorado Rockies’ business-focused advanced analytics and data science capability. This individual will be responsible for contributing to the organization’s data strategy, identifying and prioritizing high-impact data science opportunities, and independently executing advanced analytical work—including predictive, prescriptive, and machine learning models. Reporting to the Chief Revenue & Strategy Officer, the Lead Data Scientist will serve as a thought partner to leaders across the business, helping tackle complex challenges where traditional reporting is insufficient. While this role will initially have no direct reports, it is expected to play a critical role in shaping the organization’s analytics capabilities. As the analytics needs of the business evolve, opportunities for increased scope and responsibility may emerge based on organizational needs and individual performance This role is best suited for a senior individual contributor who thrives on building robust, production-ready models that drive measurable business impact rather than purely exploratory analysis. It requires a combination of deep technical expertise, strong business acumen, and clear communication skills. The Lead Data Scientist must be comfortable working hands-on across the full analytics spectrum—from advanced modeling and experimentation to select foundational analysis where needed to accelerate capability development. Their input will help define the long-term vision, structure, and standards for business analytics at the Rockies. ESSENTIAL DUTIES & RESPONSIBILITIES Advanced Analytics Execution • Design, develop, and deploy advanced analytical solutions — including predictive and prescriptive models — to address high-priority business questions across ticketing, marketing, pricing, fan engagement, partnerships, and operations. • Apply statistical modeling, machine learning, optimization, experimentation, and forecasting techniques to improve decision quality and quantify risk, uncertainty, and upside. • Translate complex analytical outputs into decision-ready insights and clear recommendations for senior leadership and non-technical stakeholders; document model assumptions and limitations to ensure appropriate application • Own projects end-to-end, from problem framing and data exploration through modeling, validation, and deployment of tools & insights into the business • Establish monitoring metrics and standards to ensure models remain relevant as data and conditions evolve. Operationalization & Model Deployment • Develop production-ready data science solutions, including APIs, scoring pipelines, and system integrations, to embed predictive and prescriptive models directly into business workflows. • Partner with IT, 601Analytics, and application owners to integrate models into CRM, pricing systems, marketing platforms, and other operational tools. • Establish version control, testing, validation, and monitoring frameworks to ensure models perform reliably in production environments. Business Partnership & Project Prioritization • Partner with the Chief Revenue & Strategy Officer and functional leaders to identify, scope, and prioritize data science initiatives aligned with organizational strategic priorities. • Build credibility and trust with stakeholders by balancing analytical rigor with pragmatic business judgment. • Work closely with Strategy and functional teammates to design and analyze experiments, test hypotheses, evaluate solution tradeoffs, and inform high-impact decisions. • Collaborate with reporting and analytics partners across the organization to ensure alignment between advanced models, core metrics, dashboards, and decision Foundational Analytics & Capability Building (Initial Phase) • Maintain primary focus on advanced modeling, experimentation, and high-impact decision support while contributing selectively to foundational analysis during early capability development. ...