Spinny

Data Scientist Intern

InternshipHybridMoga, Punjab3 months38K/mo2 openingsImmediate / Rolling

About this internship

Spinny is hiring a Data Scientist Intern in Moga — a hands-on, mentor-led internship built for students and 2026 freshers who want real exposure to data science and predictive modelling rather than a certificate-only programme. About the role As a Data Scientist Intern at Spinny, your core focus…

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Skills you'll use

Predictive ModelingA/B TestingPython / RDeep LearningStatistical AnalysisSQLPandas & NumPyData VisualisationHypothesis TestingBusiness Storytelling

What you'll do

Work on turning raw business data into models and decisions people actually act on alongside the core team
Apply Predictive Modeling, A/B Testing, Python / R, Deep 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, B.Sc/M.Sc (Statistics / Mathematics / Data Science), BCA/MCA or MBA (Analytics) — 2026 freshers & final-year students welcome
Working knowledge of Predictive Modeling, A/B Testing, Python / R (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 Moga, Punjab

Perks & benefits

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

Interview & selection process

2 rounds — typical selection flow for this role:

1Application screening & resume shortlisting by the talent team
2Online aptitude / domain assessment

About Spinny

Spinny operates in the auto e-commerce sector and has an active presence in Moga. 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…

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