SarvaGram

Data Science Intern

InternshipIn OfficePune, Maharashtra2 months44K/mo1 openingImmediate / Rolling

About this internship

Start your career in data science with SarvaGram as a Data Science Intern in Pune. You will sit with a working team, use the same tools and systems they do, and own a defined piece of work from day one. About the role As a Data Science Intern at SarvaGram, 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 Pune, Maharashtra

Perks & benefits

Letter of RecommendationMentorship from a named mentorLive project experienceExposure to professional tools and workflowsPre-Placement Offer (PPO) opportunity

Interview & selection process

2 rounds — typical selection flow for this role:

1Application screening & resume shortlisting by the talent team
2Practical assignment or case study with a short walkthrough

About SarvaGram

SarvaGram operates in the rural finance sector and has an active presence in Pune. 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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