Kaleidofin

Data Science Intern

InternshipHybridChennai, Tamil Nadu2 months26K/mo1 openingImmediate / Rolling

About this internship

Join Kaleidofin in Chennai as a Data Science Intern. This entry-level internship is designed for students and recent graduates who learn best by building, shipping and getting real feedback on data and analytics work. About the role As a Data Science Intern at Kaleidofin, your core focus will be…

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Skills you'll use

PythonMachine LearningStatisticsPandasSQLData VisualisationFeature EngineeringModel EvaluationJupyterStorytelling with Data

What you'll do

Work on turning raw data into decisions people act on alongside the core team
Apply Python, Machine Learning, Statistics, Pandas 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, Machine Learning, Statistics (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 Chennai, Tamil Nadu

Perks & benefits

Flexible working hoursNetworking with senior professionalsInternship CertificateLetter of RecommendationMentorship from a named mentor

Interview & selection process

3 rounds — typical selection flow for this role:

1Application screening & resume shortlisting by the talent team
2Practical assignment or case study with a short walkthrough
3HR discussion — stipend, start date, expectations and offer

About Kaleidofin

Kaleidofin operates in the inclusive finance sector and has an active presence in Chennai. 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…

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