
Swiggy
Data Science Intern
InternshipWork from HomeFaridabad, Haryana4 months18K/mo1 openingImmediate / Rolling
About this internship
Start your career in data and analytics with Swiggy as a Data Science Intern in Faridabad. 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 Swiggy, 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 Faridabad, Haryana
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
- 2Technical interview on fundamentals and your projects
About Swiggy
Swiggy operates in the consumer internet sector and has an active presence in Faridabad. 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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