Qualys

Data Science Intern

InternshipWork from HomeChennai, Tamil Nadu3 months23K/mo2 openingsImmediate / Rolling

About this internship

Start your career in data and analytics with Qualys as a Data Science Intern in Chennai. 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 Qualys, your core focus will be turning raw…

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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

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

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 Qualys

Qualys operates in the technology 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 work runs…

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