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Easebuzz logo — Easebuzz Marketing Machine Learning Intern in Shimla, Himachal Pradesh
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Marketing Machine Learning Intern

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Location

Shimla, Himachal Pradesh

Work Mode

Hybrid

Duration

6 months

Stipend

₹15,000/mo

Start Date

Immediate / Rolling

Openings

2 positions

Type

Full-time

Category

Machine Learning

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About the Internship

Join Easebuzz in Shimla as a Marketing Machine Learning Intern. This entry-level internship is designed for students and recent graduates who learn best by building, shipping and getting real feedback on machine learning for marketing and growth work. About the role As a Marketing Machine Learning…

About Easebuzz

Easebuzz offers a mentor-led Marketing Machine Learning Intern in Shimla with live project work in machine learning, a stipend of ₹15,000/month and a Pre-Placement Offer opportunity for strong performers.
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Shimla, Himachal PradeshVerified employer2 openings
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Skills Required

PythonPropensity & Uplift ModellingCustomer SegmentationSQLA/B TestingScikit-LearnAttribution BasicsFeature EngineeringCampaign AnalyticsBusiness Communication

Who Can Apply

  • Final-year students and recent graduates from B.E./B.Tech, MBA (Marketing / Analytics), B.Sc/M.Sc (Statistics) or MCA who are based in or willing to work from Shimla. You should be keen to learn Python, Propensity & Uplift Modelling, Customer Segmentation on real projects and able to write clearly. Freshers are welcome — no prior work experience is required, and a strong project portfolio matters more than a long CV.

Perks

Mentorship from a named mentorLive project experienceExposure to professional tools and workflowsPre-Placement Offer (PPO) opportunityFlexible working hours

Interview & Selection Process

3 rounds — typical selection flow for this role:

  1. 1Application screening & resume shortlisting by the talent team
  2. 2Technical interview on fundamentals and your projects
  3. 3HR discussion — stipend, start date, expectations and offer
15,000/month

Stipend · 6 months

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Openings2 positions
Applicants0 applied
ModeHybrid
CategoryMachine Learning
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