Most internship listings promise you'll "learn analytics." Fewer of them explain what that actually looks like on a Tuesday afternoon. This one does. It's a fully remote, entry-level position where the deliverables you produce- dashboards, cleaned datasets, weekly summaries- get used by real teams, not filed away as practice work.
The Short Version
You'll spend your time pulling data together, running it through basic SQL or spreadsheet logic, and turning the results into something a marketing manager or product lead can actually use. Nobody expects polish on day one. What matters is that you show up willing to be corrected, then apply the correction the next time.
How the Work Breaks Down
Data support takes up a good chunk of the week. You'll gather information from multiple sources, clean it, and put it into a usable format, then run queries or spreadsheet filters to pull out the subset the team actually needs. From there, senior analysts will lean on you to help prep the visual side of reporting.
There's also a metrics and dashboarding piece. Expect to track a handful of key performance indicators, build out beginner-level dashboards in Power BI or Tableau, and summarize what the numbers are saying in plain language, no jargon, no ten-slide decks nobody reads.
A smaller but steady part of the job is documentation. Notes get outdated fast if nobody maintains them, so you'll help keep process docs current and log changes as you make them. It sounds tedious. It saves everyone time later.
Qualifications
Minimum education:
High school diploma or equivalent. If you're currently enrolled in or recently finished a degree in a STEM field, economics, or business, that's a plus, but it isn't a hard requirement.
Minimum experience:
0 to 6 months. This doesn't have to mean a job title. Coursework, a self-directed project, volunteer data work, any of that counts.
Past that baseline, here's what tends to separate a strong candidate from an average one:
- Basic comfort with spreadsheet formulas and how data is typically structured
- An eye for detail, the kind that catches a mislabeled column before it becomes a problem
- Real curiosity about how numbers translate into decisions
- The self-discipline to manage your own hours without someone checking in every day
Nice-to-Haves
None of the following will disqualify you if you're missing them. But they help:
- Some exposure to SQL, even a beginner course counts
- A rough grasp of statistical terms like mean, median, or standard deviation
- Prior coursework or an internship touching data or business analysis
Tools You'll Actually Touch
Excel and Google Sheets for the day-to-day formatting work. SQL when you need to pull from a relational database instead of a spreadsheet. Tableau or Power BI for the dashboards, and occasionally Google Data Studio for lighter, automated reports. On the communication side, it's Slack and Zoom for check-ins, Google Docs for anything that needs to be written down and shared.
Pay and Schedule
The stipend is set at $50,809 annualized, with a weekly time commitment of 20 to 25 hours. Internships run 3 to 6 months and the schedule flexes around your availability. There's no office to report to, ever, and your working hours are yours to arrange as long as deadlines and scheduled meetings get hit.
What You Actually Get Out of It
- Fully remote, with zero relocation or commuting involved
- Flexible hours that work around classes, another job, or whatever else is going on
- Weekly mentoring with someone who's actually done this work
- Training folded into the schedule rather than treated as an afterthought
- A portfolio of dashboards and reports you can point to in future interviews
- First consideration if a full-time remote analytics role opens up down the line
Who You'll Be Working With
The team is remote-first but not remote-isolated. You'll be paired with analysts, marketing folks, and product managers, so you'll see how the same dataset is read three different ways depending on who's looking at it. That cross-functional exposure is honestly one of the more underrated parts of the role. Candidates browsing openings through Naukri Mitra often ask what makes an internship worth their time, and the honest answer here is the feedback loop: it's frequent, it's specific, and it's meant to actually improve your work rather than just check a box.
There's also an intern cohort you'll be part of, people at a similar stage, working through similar problems, comparing notes.
A Typical Week
Monday brings a task brief and a rough set of goals. Midweek, you'll meet with a mentor to talk through what's working and what isn't. By Friday, send out a summary and whatever you've finished. It repeats, but the tasks inside it don't stay the same for long.
By the End of This
You should be able to clean a dataset without hand-holding, build a dashboard that someone outside the data team can actually understand, and explain your reasoning out loud without losing the room. You'll also pick up the basics of data integrity and why it's taken so seriously in most companies.
Ready to Apply?
Students, recent grads, and career changers, all welcome. You don't need a résumé full of analytics jobs. You need to be curious about data and disciplined enough to manage a remote schedule without someone standing over your shoulder.
Open to applicants from the United States, Canada, the United Kingdom, the European Union, Australia, India, and other eligible regions. Send in your application when you're ready.
