Sprinklr

Data Science Intern

InternshipIn OfficeNagpur, Maharashtra6 months45K/mo3 openingsImmediate / Rolling

About this internship

Sprinklr has an open Data Science Intern position in Nagpur for motivated freshers and final-year students. You will work on live data science projects and finish with something you can genuinely talk about in interviews. About the role As a Data Science Intern at Sprinklr, your core focus will be…

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Skills you'll use

PythonSQLStatisticsMachine LearningPandasData VisualisationPower BI / TableauHypothesis TestingExcelStorytelling with Data

What you'll do

Work on extracting insight and building predictive models from real data alongside the core team
Apply Python, SQL, Statistics, Machine Learning 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, SQL, 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 Nagpur, Maharashtra

Perks & benefits

Networking with senior professionalsInternship CertificateLetter of RecommendationMentorship from a named mentorLive project experience

Interview & selection process

3 rounds — typical selection flow for this role:

1Application screening & resume shortlisting by the talent team
2Discussion with the hiring manager on the role and your fit
3HR discussion — stipend, start date, expectations and offer

About Sprinklr

Sprinklr operates in the saas sector and has an active presence in Nagpur. 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 at…

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