Every fraction of a second an athlete shaves off, every injury that gets caught before it happens, traces back to someone who looked at a pile of numbers and figured out what they actually meant. We're hiring a
Remote Athlete Performance Analyst to be that person for our teams — turning wearable data, motion capture, and physiological testing into recommendations coaches will actually use, not just file away.
The job, plainly
You'll pull data from GPS units, heart rate monitors, EMG sensors, and VO2 max testing, then figure out how to reconcile it, since different systems tend to measure the same thing in slightly different ways. From there it's statistical analysis, then reporting, then the part that actually matters: getting a finding in front of a coach or medical staffer while there's still time to act on it. This is a fully remote role paying $86,608 a year.
Most of what lands on your desk won't be clean. Wearables drop readings, sensors disagree with each other, and someone will inevitably ask you to reconcile three seasons of data that were collected on three different systems. Part of the job is being unbothered by that.
What you'll be doing
Data work makes up the base of the job — structuring datasets, standardizing formats across sources so a season's worth of numbers still means something two years later, and running the kind of statistical analysis that catches a fatigue pattern before it turns into a hamstring pull. From there:
- Compare current athlete metrics against historical baselines and league-wide benchmarks
- Build dashboards in Tableau, Power BI, or Looker that a coach can read without a data science background
- Join remote strategy sessions with coaching staff, sports scientists, and medical teams
- Keep databases clean and secure enough that nobody has to second-guess last season's numbers
- Spot early injury or fatigue risk and say something before it becomes a problem, not after
What you need coming in
This isn't an entry-level analytics role. You should have a bachelor's degree in sports science, data analytics, exercise physiology, or a related field, along with at least 2 years of experience in athlete monitoring, sports analytics, or performance consulting. On the technical side, working knowledge of R, Python, or MATLAB matters, and so does SQL — you'll be querying performance databases regularly enough that this can't be a rusty skill. Beyond the tools, you need a real grasp of sports-specific KPIs and biomechanics, and the ability to walk a coach through a regression result without losing them in the first sentence.
A master's degree isn't required, but many candidates for roles like this have one, and it won't hurt your application if your experience doesn't fully compensate for its absence.
What sets a candidate apart
Hands-on time with GPS systems like Catapult or STATSports counts for a lot here, as does any exposure to motion capture cameras or other biomechanical evaluation equipment. If you've worked with machine learning techniques — clustering, predictive modeling — applied specifically to athletic data, mention it. Same goes for experience presenting to executives who don't have patience for jargon, and for having worked with elite, professional, or collegiate athletes rather than a general fitness population. None of these are hard requirements. They're just things that move an application to the top of the pile. We'd rather see one deep, specific example — a project where your read on the data changed how a team trained or recovered — than a long list of tools you've briefly touched.
Who you'd be working with
The team is a distributed network of analysts, trainers, and coaches spread across time zones, coordinating mostly through Slack and Zoom. There's no meaningful hierarchy separating a junior analyst's observation from a senior one's — if the data backs it up, it gets heard. Roles
like this are often posted on platforms like Naukri Mitra, mainly because candidates who combine sports science training with real statistical skills aren't easy to find through a generic job board search.
Hours flex around competition schedules rather than sitting fixed at nine to five. Expect heavier weeks around game days and lighter ones in the off-season, along with a general preference for writing things down over scheduling another call. Nobody's tracking whether you were online at 9 am sharp — they're tracking whether the fatigue report was ready before Monday's training session.
What good work looks like here
Nobody's judging you on how many charts you produce. What matters is whether a coach changes a decision because of what you found: pulling an athlete back before a minor strain becomes a real injury, or catching a drop-off in readiness three weeks before it would've shown up in a game. The analysts who do well here don't just hand off a report and move on — they check back a week or two later, see whether the numbers moved the way they predicted, and say so plainly when they didn't.
Compensation and where this can go
- $86,608 annual salary, open to remote candidates regardless of where they're based
- Funding for certifications on sports tech platforms and travel to international sports analytics conferences
- Scheduling built around athlete and project milestones instead of a rigid office clock
- A real path toward specializing in biomechanics, sports psychology, or AI-driven performance tracking
Analysts who show consistent impact tend to move into leading cross-functional initiatives within a year or two — that's not a recruiting line, it's just what's happened with the people who've done well in this role before.
Applying
Send your resume along with a short write-up of one analysis you're genuinely proud of, including what it actually changed for the athlete or team involved. We care more about how you think through a problem than what's listed on a certification page. Applications are open worldwide, including in the United States and India, though it's worth checking our global hiring locations page first for any country-specific details.
