Concessions ran short in section 214 last Saturday. Nobody planned for that. Staffing was thin during a sellout crowd two weeks before that. Somebody has to catch these things before they repeat. That's the job. We're hiring a
Remote Sports Operations Data Analyst.
About the Role
Messy data comes in — game logistics, ticket sales, athlete performance, fan engagement — and you turn it into something operations can actually use. This isn't analysis for the sake of a report nobody reads. Staffing calls, inventory decisions, scheduling changes all trace back to what you find.
What Fills the Day
Pulling data first. Internal databases, outside APIs, structured and unstructured, cleaned up before anyone trusts a single number in it. Pipelines are built and automated so nobody has to do a manual pull every time a question comes up. Then the analysis — statistical work, dashboards, usually in Tableau or Power BI, looking for whatever pattern actually changes a decision instead of just sitting in a report. Presenting it well matters just as much as finding it. Coaching staff and executives want something they can read in two minutes, not a spreadsheet dump.
What Gets You Considered
A Bachelor's degree in Data Science, Sports Management, Statistics, Computer Science, or something in that family. That's the education floor. On experience — two years minimum as a data analyst or operations analyst.
- Bachelor's degree in Data Science, Sports Management, Statistics, Computer Science, or related field
- 2+ years as a data analyst or operations analyst
- Solid SQL, one analytics language on top — Python or R
- Has actually built dashboards in Tableau or Power BI, not just watched a demo
- Can explain a dataset to someone who doesn't work with data for a living
Doesn't hurt if you've got: time in sports or entertainment specifically, exposure to team logistics or fan attendance data, some background in forecasting or machine learning.
How the Work Runs
Fully remote. Structured around your own productive hours, not a fixed shift. Sports operations rarely look the same two days in a row, so flexibility beats a rigid process here. This one's posted in a few spots right now, including Naukri Mitra. Application review stays the same regardless of source.
Tools You'll Use
SQL for pulling data. Python or R for modeling and automating the boring parts. Tableau, Power BI, or Looker for visuals. Google Sheets or Excel when something needs to move fast. AWS or Google Cloud for storage. Sports data APIs and a few proprietary systems specific to this industry.
Pay and What's Included
The role pays
$96,500 a year.
- Comprehensive health benefits
- Paid time off, personal and professional
- Home office stipend, ergonomic support
- Sports analytics webinars and courses
- Yearly development allowance, performance bonuses
Where It Can Lead
Deliver work that actually changes decisions, and it opens doors — leading data strategy, specializing in predictive modeling, moving into project management. Mentoring newer analysts too, once seniority's there.
Apply
Open to the U.S., Canada, the UK, the EU, Australia, India, and a handful of other regions. Send a resume. An example dashboard or analysis, if you've got one worth showing, says more than any list of tools would.
