Nanonets

Data Science Intern

InternshipIn OfficeGurugram, Haryana4 months41K/mo1 openingImmediate / Rolling

About this internship

Nanonets is hiring a Data Science Intern in Gurugram — a hands-on, mentor-led internship built for students and 2026 freshers who want real exposure to data science rather than a certificate-only programme. About the role As a Data Science Intern at Nanonets, your core focus will be building…

Skills you'll use

PythonStatisticsMachine LearningPandas & NumPySQLData VisualisationHypothesis TestingScikit-learnJupyterBusiness Acumen

What you'll do

Work on building predictive models and extracting insight from real datasets alongside the core team
Apply Python, Statistics, Machine Learning, Pandas & NumPy to live, production-facing problems
Document your work clearly for reviewers and stakeholders
Participate in reviews and act on the feedback you receive
Collaborate across engineering, product, design or business as required
Follow the team's quality, testing and documentation standards

Who can apply

Pursuing or recently completed B.E./B.Tech/M.Sc (Statistics, Maths)/MCA/MBA (Analytics) — 2026 freshers & final-year students welcome
Working knowledge of Python, Statistics, Machine Learning (or a genuine willingness to learn them)
Strong fundamentals in your discipline and clear problem-solving ability
Care with detail and the discipline to document your work
Clear written and verbal communication in English
Based in or willing to work from Gurugram, Haryana

Perks & benefits

Exposure to professional tools and workflowsPre-Placement Offer (PPO) opportunityFlexible working hoursNetworking with senior professionalsInternship Certificate

Interview & selection process

2 rounds — typical selection flow for this role:

1Application screening & resume shortlisting by the talent team
2Team-fit / behavioural interview with the team

About Nanonets

Nanonets operates in the document ai sector and has an active presence in Gurugram. Interns here are put on real work from the start, because the team's view is that the fastest way to learn a craft is to practise it under people who already do it well — not to watch it from a distance. The work…

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