Data Scientist

We are looking for a detail-oriented, analytical, and technically curious individual to join Eventellect's Data Science team as a Data Scientist, Seat Quality.

The ideal candidate will combine strong analytical problem-solving skills with a technical foundation, a process-oriented mindset, and the ability to manage a steady flow of requests efficiently and accurately. This person will take ownership of building and maintaining data-driven models, investigating unexpected results, and using analytical judgment to ensure outputs are reliable and consistent with business expectations.

We are looking for someone who is comfortable working with large datasets, learning complex technical workflows, and thinking critically rather than simply following a prescribed process. Experience using programming and data analysis tools such as Python and SQL, along with an interest in further developing technical skills through scripting, debugging, and application development, will be valuable in this role. Strong attention to detail, sound judgment, and the ability to work independently are essential.

As a Data Scientist on Eventellect's Seat Quality team, you will support the development, maintenance, and ongoing improvement of data-driven models and the technical tools that support them. You will work closely with Data Science leadership and cross-functional teams to fulfill modeling requests, troubleshoot data and modeling issues, and ensure outputs are accurate, reliable, and aligned with business needs.

The role will primarily focus on executing recurring modeling workflows and responding to ad-hoc requests, with opportunities to take on more advanced technical responsibilities, including model investigations, application development, and process improvements.

• →Build, retrain, and maintain data-driven models across professional sports, collegiate athletics, concerts, and other live events.
• →Manage a recurring queue of modeling requests, balancing accuracy, efficiency, and competing priorities to deliver reliable results on time.
• →Evaluate and validate model outputs, using analytical judgment to identify unexpected patterns, inconsistencies, and potential modeling issues.
• →Investigate and troubleshoot data quality issues, inconsistencies in underlying inputs, and unexpected model behavior.
• →Execute ad-hoc analytical and modeling requests, including model adjustments, data updates, and corrections to existing outputs.
• →Leverage Python, SQL, and internal data tools to investigate discrepancies, manipulate datasets, and support modeling workflows.
• →Develop proficiency with Eventellect's internal applications, data infrastructure, and technical processes to independently execute and validate modeling work.
• →Collaborate with internal stakeholders to understand requirements, resolve data issues, communicate blockers, and ensure outputs meet business needs.
• →Contribute to the maintenance and development of internal applications, including debugging, implementing enhancements, and improving existing functionality.
• →Identify opportunities to improve the efficiency, reliability, and scalability of modeling workflows through automation, technical improvements, and process optimization.

• Bachelor’s degree in data science, computer science, statistics, mathematics, analytics, or a related quantitative field
• Strong analytical skills and a curiosity to investigate unexpected results, troubleshoot issues, and anticipate the downstream impacts of decisions
• Familiarity with programming and data analysis tools such as Python, SQL, or similar technologies
• Demonstrated attention to detail and the ability to execute complex, multi-step technical workflows accurately and independently
• Ability to manage competing priorities while balancing efficiency, accuracy, and timely delivery
• Capacity to learn new technical systems quickly, adapt to unfamiliar challenges, and collaborate across internal teams

• Hands-on experience writing Python scripts and apps or automating analytical workflows
• Experience with data modeling, statistical analysis, machine learning, or model validation
• Exposure to Git, version control, debugging, or software development workflows
• Familiarity with ticketing, live events, sports analytics, or related industries