JM Financial

Data Science Intern

InternshipHybridMumbai, Maharashtra6 months23K/mo4 openingsImmediate / Rolling

About this internship

JM Financial is hiring a Data Science Intern in Mumbai — a hands-on, mentor-led internship built for students and 2026 freshers who want real exposure to data and analytics rather than a certificate-only programme. About the role As a Data Science Intern at JM Financial, 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 Mumbai, Maharashtra

Perks & benefits

Internship CertificateLetter of RecommendationMentorship from a named mentorLive project experienceExposure to professional tools and workflows

Interview & selection process

3 rounds — typical selection flow for this role:

1Application screening & resume shortlisting by the talent team
2Technical interview on fundamentals and your projects
3HR discussion — stipend, start date, expectations and offer

About JM Financial

JM Financial operates in the investment banking sector and has an active presence in Mumbai. 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…

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