Analyst

Houston Rockets -- Toyota Center•Houston, TX

13d•Onsite

About The Position

This position uses advanced quantitative and qualitative analytical methods to provide actionable insights and solutions to complex business challenges through data visualization, modeling, and structured reporting. The department’s primary function is to accelerate growth and success for the business units, while enabling data-driven decisions across the company, including the Houston Rockets, Houston Comets and Toyota Center.

Requirements

Bachelor’s degree in data science, Business Analytics, Computer Science, Engineering, Information Systems, Statistics, Economics, or a related field
1-3 years of experience in analytics, business intelligence or strategy.
Strong written and verbal communication skills, including the ability to convey complex results in a clear, concise, and credible manner
Team player with time management skills and the ability to multi-task within a fast-paced environment
Curious self-starter who learns new concepts quickly
Highly analytical person with strong problem-solving skills and attention to detail
Advanced critical thinking and project management skills
Deep understanding of statistical and forecasting principles
Foundational computer skills (Microsoft Word, Excel, Power Point, Outlook, Teams)
Proficient in data visualization tools (Tableau is required)
Fluent in SQL programming for database management
Experienced in a general purpose or statistical programming language (R, Python, etc.)
Fundamental understanding of predictive modeling, structured analytic methodologies, and AI/automation

Nice To Haves

Previous sports and/or live entertainment experience preferred.
Recent graduates with a relevant degree or academic experience are encouraged to apply.

Responsibilities

Design, implement and maintain data visualizations, structured reports, and ad hoc audits for all lines of business, including both operational and performance metrics.
Conduct comprehensive data analysis to inform strategic business decisions. Methodologies may include descriptive, regression, dispersion, factor, and time series analysis.
Develop and train internal predictive statistical models to identify opportunities, mitigate risks and inform our business strategy. Model structures include Relational, Hierarchical, and Network data models.
Partner with data engineers, business partners, and technology vendors to acquire, structure and manage data from multiple platforms and applications.
Leverage multiple programming languages (SQL, R, Python, etc.) to query, connect, and validate data across multiple domains.
Adhere to data quality standards, actively identify and resolve inaccuracies, and maintain a continuous improvement approach.
Enhance efficiency through automation, AI, and modernized tech solutions.
Proactively identify objectives where leveraging data, analytics, and visualizations will drive a measurable impact through thoughtful collaboration with primary stakeholders across the organization.
Maintain, adjust and communicate consistent data entry processes used by internal stakeholders. Mentor stakeholders on subject matter knowledge and processes to ensure they are repeatable, sustainable, and scalable.
Identify opportunities to improve productivity and efficiency through process enhancement, documentation and data accuracy.
Demonstrates our One Team philosophy of Passion, Accountability, Customer Focus, and Teamwork.