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Ticketing Data Science Representative
San Antonio Spurs

EXPIRED

EXPIRED

Application Deadline Ended


Apply by Ended 9/2/2023

Ticketing Data Science Representative

San Antonio Spurs

Posted 7 months ago

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Location


San Antonio, TX, USA

Job Type


Job Description

The Ticketing Data Science Representative will be responsible for the design, implementation, and reproducibility of end-to-end data science solutions (data collection/processing, visualization, analysis, modeling, deployment/communication) to support the Ticket Operations department. This opportunity will provide the selected candidate with a wide understanding of how professional sports organizations apply data to make decisions regarding revenue generation and customer experience.

In every position, each employee is expected to: demonstrate alignment with SS&E’s core values and mission, collaborate with internal/external family members and demonstrate ongoing development.

Responsibilities

  1. Demonstrate the ability to collect/clean/store/manage data, perform data exploration/analysis/modeling, and communicate insights to non-technical shareholders.
  2. Collaborate with various departments on assigned ticketing projects and perform ad hoc analysis.
  3. Develop or refine the processes currently used by Ticket Analytics to ensure that high-quality results are achieved.
  4. Other duties as assigned.

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Qualifications Required

  • Display a passion for working with data and exhibit enthusiasm for learning new concepts
  • Strong analytical and problem-solving skills
  • Excellent verbal and written communications skills
  • Proficiency in Python or R required
  • Proficiency in Microsoft Office, SQL, BI visualization tools (Tableau/Power BI/etc.) preferred
  • Ability to demonstrate professionalism and be proactive in communication with the Ticketing Analytics team
  • 100% of work can be done remotely
  • An undergraduate or graduate degree in business analytics, computer science, statistics, mathematics, economics or other closely related technical field preferred.

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