Sales, Service, & Marketing: Financial/Data Analyst
Senior Business Analyst - Charlotte Hornets (Charlotte, NC)

Position Overview

The Senior Business Analyst performs quantitative and strategic analyses in support of revenue generating departments of the Charlotte Hornets. You will provide data analysis and reporting to inform decision-making on multiple subjects including; ticket pricing, revenue forecasting, surveying, profitability analyses, customer segmentation, and sales lead scoring.

Required Skills, Experience, and Abilities

To perform the job successfully, you should demonstrate the following competencies

  • Bachelor and Master's degree in mathematics, computer science, statistics, or data sciences from an accredited college or university
  • 2+ years of expertise with statistical software packages in a data science environment (R, Python, SQL, etc) - we are looking for more than just advanced Excel skills
  • Expertise in analyzing data and building predictive models inside a statistical computing environment (e.g., R, SPSS, Matlab, Octave)
  • Proficiency in statistical modeling techniques such as linear regression, logistic regression, GLM, tree models (CART, MART, CHAID), cluster analysis, principal components, validation, and feature creation.
  • Experience working with big data and supervised and unsupervised machine learning
  • High-level of experience with business visualization programs (Tableau, Business Objects, Domo, etc)

Essential Duties and Responsibilities

  • You will locate new data sources, analyze statistics, and implement quality procedures
  • Discover "stories" told by the data and present them to both internal and external business partners
  • Provide cross-functional decision support to partners within the organization offering analyses and simulations to better inform business decisions.
  • You will collaborate with department leaders across the organization; including Sales, Sponsorship, Marketing, and Database Marketing
  • You will enrich our digital assets, build big data analytics capabilities, and partner with all departments to add new value to our strategic initiatives, ultimately driving fans, revenue growth and return on investment
  • Develop requirements, outlines, budgets, and schedulers for projects.


  • You will perform revenue forecasting and trend analysis on ticket sales
  • Utilize primary and secondary market ticket data to make ticket pricing recommendations
  • Evaluate customer demand for products and their price elasticity
  • Track customer behavior to analyze fan segments and customer lifetime value
  • You will evaluate buying behavior trends across marketing channels to make recommendations for effectiveness of various marketing tactics and campaigns
  • Make digital marketing recommendations based on investigation of email performance statistics
  • Integrate numerous sources of customer behavior data to segment and prioritize existing and prospective buyers to create scouting reports for the multiple departments
  • You will analyze product sales, track performance metrics and provide updated dashboards for all levels of management
  • Analyze customer engagement and behavior for UI design, and generate mobile ordering revenue reports for management

We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.

Note: This position was originally posted on the Charlotte Hornets employment site. To ensure that your application is considered for this position, please click here to apply for this job on the Charlotte Hornets employment site.

Note: When you apply for this job online, you will be required to answer the following questions:

1. Please describe your “go-to” statistical software programs you like to use and your level of expertise.
2. Please describe your experience your work building “unsupervised machine learning” algorithms.
3. Please describe your experience building pricing models.
4. Please describe your experience working in R.
5. Please describe your experience working with large data sets and transforming the data into a workable format.

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