The hard part of hiring a single Data Science intern is not finding applicants. It is writing a brief specific enough that the right applicants recognise themselves in it.
The "ML" qualifier means evaluation is part of the deliverable. A model with no held-out evaluation is not a deliverable, and screening should test that instinct directly.
People searching for data science ml intern often also look at data scientist intern. The skills overlap heavily; what differs is emphasis — this brief leans on the ml side of the work, while data scientist intern leans on scientist. If your requirement genuinely spans both, say so in the listing rather than picking one title and hoping.
Below: the skills worth testing, the work a student can genuinely finish in a term, 2026 stipend bands, and questions that have a wrong answer. Posting is free and takes about two minutes.
What a single Data Science intern actually does in the first 90 days
Each of these is work a team member would otherwise do. That is the test of a good intern brief: real work already on someone's list, not a project invented to keep the intern busy.
- Build a baseline, beat it, and document why the improvement is real
- Build a baseline model and beat it, documenting both
- Ship one analysis that changes a decision, not just a notebook
- Write the data dictionary and reproducible pipeline for the dataset you used
Data Science skills worth screening for
Screen on the first three. The rest are teachable inside a term, and treating them as entry requirements shrinks your pool for no gain.
- 1Train/test discipline and leakage awareness
- 2Framing a business question as a modelling problem
- 3Exploratory analysis and feature engineering
- 4Train/test discipline and leakage avoidance
- 5Model evaluation beyond accuracy
- 6Pandas and NumPy fluency
- 7Communicating uncertainty
- 8Notebook hygiene and reproducibility
The tools column is where CV inflation happens. Pick two and ask what went wrong the last time they used them; the answer is unfakeable.
Screening questions for data science ml intern
These separate practice from theory. Ask two, listen for a specific example, then follow the example rather than moving to the next question.
What is data leakage and how would you catch it?
What a good answer shows: The mistake that invalidates most student projects
Your model is 95% accurate on a 5% event rate. Is it good?
What a good answer shows: Whether they see the base-rate trap
How would you explain a model to a sales director?
What a good answer shows: Translation ability
Score every candidate on the same questions. Comparing free-form conversations across a shortlist is where inconsistency, and bias, get in.
Where the Data Science candidates come from
MyInternships.in carries a verified, India-wide pool of students and fresh graduates — from IITs, NITs, BITS, IIMs and Symbiosis through to strong regional engineering and commerce colleges. Profiles carry skill tags, so you can filter on Python and pandas and NumPy rather than reading résumés.
- Skill tags — filter directly on Python, pandas and NumPy, scikit-learn and the rest of the Data Science stack
- Availability window and notice, so a six-month role does not shortlist a six-week candidate
- Degree and branch, for the roles where the coursework genuinely matters
- Languages, for roles with customer or field contact across states
- Prior data science exposure — coursework, personal projects or a previous internship
Skill tags come from the candidate’s own projects and verified profile, so filtering on Python or pandas and NumPy returns people who have used them rather than people who listed them.
What to pay a single Data Science intern in 2026
₹18,000–₹45,000 a month is the band we see for this role across India. The spread is mostly city and company stage, not candidate quality.
It filters for who can afford to work free, not who is good. It also roughly halves your applications, and removes most of the candidates who had a second option.
Bengaluru, Hyderabad, Pune, Mumbai, Gurugram and Noida sit at the top of the band. Tier-2 cities typically run 25–40% lower for the same skills and the same output.
The stipend calculator on this site uses live listing data for this role and city. A band chosen from memory is usually a year out of date, always in the same direction.
Six-month commitments generally command more per month than six-week ones, because the candidate is giving up other options. Price the commitment, not just the hours.
Getting one Data Science intern to actually produce something
The difference between an intern who ships and one who does not is almost never talent. It is whether the work was ready on their first day and whether someone read it on their second week.
Laptop, accounts, repository or dataset access, and a task small enough to finish in two days. Interns who spend week one waiting for access rarely recover the momentum.
Read their work in the first week, not the fourth. Early correction on a small piece of Data Science work is cheap; late correction on a term’s work is not.
Someone who wants the output and will complain if it is wrong. Work with no audience is the fastest route to a disengaged intern.
Write down what a successful term would produce. Otherwise the end-of-term assessment becomes a memory of impressions, and that helps nobody.
How to post data science ml intern on MyInternships.in
You do not need a prepared job description. Answer a few questions in the chat and the assistant drafts the listing, title and skill tags for you.
Describe the role the way you would to a colleague: what the data science work is, how long for, and what you can pay. The assistant asks the rest.
You get a full Data Science listing back in seconds, written to attract applications rather than to satisfy a form. Change anything you disagree with.
We check the company behind every listing before it publishes. Candidates see that badge, and it is the difference between a listing being ignored and being answered.
Expect the first responses the same day. Shortlist against the questions above, then interview — most roles here close inside two weeks.
Free plan: one listing, live after verification. Starter ₹499: five listings a month, published instantly, full applicant contact and résumé access. Growth ₹999: fifteen listings with AI candidate matching.
Mistakes that cost you the good Data Science candidates
Four failures we see repeatedly on this kind of role, in rough order of what they cost.
A Data Science listing with fourteen required tools reads as a company that does not know what it needs. Strong candidates self-select out; the ones who apply anyway have inflated their CVs to match.
CGPA has almost no relationship with output in this role. One project they can explain in depth, including what went wrong, predicts far better.
"Assist the team" tells a candidate nothing and tells you nothing at review time. Name the work, in the listing, from the deliverables above.
Interviews reward confidence, and confidence in early-career candidates is distributed unevenly by background rather than by ability. Score the answers, not the delivery.
Data Science ML Intern — frequently asked questions
Which Data Science skills are non-negotiable for data science ml intern?+
Insist on train/test discipline and leakage awareness, and on enough framing a business question as a modelling problem to work unsupervised on small tasks. Exploratory analysis and feature engineering is the third thing worth testing in the interview. Tool familiarity — Python, pandas and NumPy, scikit-learn — is a bonus rather than a filter: most of it is a week of learning for someone with the underlying skill.
Is data science ml intern enough to move a real project forward?+
Yes, within a scoped brief. Build a baseline, beat it, and document why the improvement is real is achievable in a term with weekly review, and it is genuine output rather than a training exercise. What does not work is open-ended ownership of anything with production consequences — keep the judgement calls with the reviewer and the execution with the intern.
What stipend should we pay data science ml intern in India?+
₹18,000 to ₹45,000 a month covers most of the market for this role. Metro product companies pay at the top of the band; tier-2 cities and services firms 25–40% lower. An unpaid listing filters for who can afford to work free rather than who is good, and roughly halves the applications you receive.
What is the fastest way to tell a strong Data Science candidate from a weak one?+
Ask about something that went wrong. "What is data leakage and how would you catch it?" gets you the mistake that invalidates most student projects, and two follow-up questions on their own example will tell you the depth. Candidates who have only studied the topic run out of specifics almost immediately.
What does it cost us in time to supervise one Data Science intern?+
Realistically two to four hours a week of a competent person: a longer session early on, then short daily availability and a weekly review. Below that, the intern stalls and produces nothing you can use. Above it, you are doing the work yourself. That time is the true cost of the hire, and it is what the stipend line in your budget does not show.
Does the "Ml" in Data Science ML Intern change who we should hire?+
The "ML" qualifier means evaluation is part of the deliverable. A model with no held-out evaluation is not a deliverable, and screening should test that instinct directly. In screening terms, that means adding one specific check: train/test discipline and leakage awareness.
Is posting data science ml intern on MyInternships.in free?+
Yes. One listing is free and goes live after a quick company verification, usually inside two working days. Paid plans start at ₹499 for five postings a month, publish instantly with no review wait, and unlock every applicant's résumé and contact details. Both routes reach the same candidate pool.
Should the listing state the duration and start date?+
Always. Students plan around semester dates, and a listing without a start date and duration is filtered out by exactly the organised candidates you want. For Data Science roles, stating "three months, starting June" typically produces more applications than an open-ended listing at a higher stipend.
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