Locus.sh
Data Science Intern
InternshipHybridBengaluru, Karnataka2 months26K/mo1 openingImmediate / Rolling
About this internship
Locus.sh is hiring a Data Science Intern in Bengaluru — a hands-on, mentor-led internship built for students and 2026 freshers who want real exposure to data science rather than a certificate-only programme.
About the role
As a Data Science Intern at Locus.sh, your core focus will be building…
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Skills you'll use
PythonStatisticsMachine LearningPandas & NumPySQLScikit-learnHypothesis TestingData VisualisationJupyterBusiness Acumen
What you'll do
- Work on building predictive models and experiments on real product data alongside the core team
- Apply Python, Statistics, Machine Learning, Pandas & NumPy 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 Bengaluru, Karnataka
Perks & benefits
Exposure to professional tools and workflowsPre-Placement Offer (PPO) opportunityFlexible working hoursNetworking with senior professionalsInternship Certificate
Interview & selection process
2 rounds — typical selection flow for this role:
- 1Application screening & resume shortlisting by the talent team
- 2Online aptitude / domain assessment
About Locus.sh
Locus.sh operates in the supply chain saas sector and has an active presence in Bengaluru. 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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