Quantiphi

Data Science Intern

InternshipIn OfficeMangaluru, Karnataka6 months19K/mo4 openingsImmediate / Rolling

About this internship

Start your career in data science with Quantiphi as a Data Science Intern in Mangaluru. 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 Quantiphi, your core focus will be extracting…

Skills you'll use

PythonStatisticsMachine LearningPandasSQLData VisualisationHypothesis TestingScikit-learnJupyterBusiness Acumen

What you'll do

Work on extracting insight and building predictive models from real datasets alongside the core team
Apply Python, Statistics, Machine Learning, 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, 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 Mangaluru, Karnataka

Perks & benefits

Pre-Placement Offer (PPO) opportunityFlexible working hoursNetworking with senior professionalsInternship CertificateLetter of Recommendation

Interview & selection process

2 rounds — typical selection flow for this role:

1Application screening & resume shortlisting by the talent team
2Technical interview on fundamentals and your projects

About Quantiphi

Quantiphi operates in the data science & analytics sector and has an active presence in Mangaluru. 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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