Lead Data Scientist, Business Analytics

This is a Full Time Job

Lead Data Scientist, Business Strategy & Analytics

ABOUT US

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.
• Help establish best practices for documentation, reproducibility, data quality, and analytical rigor across projects.
• Partner to coach and develop analytics capabilities of existing teammates and to build functional leaders' comfort leveraging data and analytics to lead their teams.

Data Strategy & Analytics Vision
• Contribute to the development of a long-term vision for business analytics at the Rockies, spanning advanced data science and scalable reporting and insight delivery capabilities.
• Partner closely with 601Analytics and internal data engineering resources to leverage a modern, scalable data warehouse environment, ensuring advanced models are built on reliable, well-governed data assets.
• Partner with IT and data engineering/architecture teams to ensure data science solutions are scalable, sustainable, and aligned with enterprise data strategy.
• Establish and adhere to documentation and file management standards to ensure tools and analyses can be efficiently maintained and evolved over time.
• Stay current with emerging techniques and data sources in data science, machine learning, and artificial intelligence, identifying opportunities to apply these tools aggressively yet responsibly-with appropriate governance, transparency, and risk management-to drive meaningful business impact.

Communication & Leadership
• Clearly communicate analytical findings through written, visual, and verbal formats tailored to technical and non-technical audiences.
• Exceptional problem-solving and critical-thinking skills, with the ability to connect analytical work to real business outcomes.
• Strong business acumen and curiosity about how organizations operate, generate revenue, and serve customers.
• Excellent communication skills, including the ability to explain complex concepts clearly and concisely to non-technical audiences.
• Proven ability to collaborate cross-functionally, manage competing priorities, and operate effectively in a fast-paced, evolving environment.
• Comfort working in ambiguity and helping design processes, standards, and structures where none previously existed.

JOB QUALIFICATIONS:
• Bachelor's degree in Data Science, Statistics, Economics, Mathematics, Computer Science, Business Analytics, or a related quantitative field required.
• Master's degree or PhD preferred.
• 7 years of progressive experience in data science, advanced analytics, or a related analytical role within a business, sports, media, or consumer-facing environment.
• Demonstrated experience independently leading complex, ambiguous analytical projects.