Location
Faridabad, Haryana
Work Mode
In Office
Duration
3 months
Stipend
₹17,000/mo
Start Date
Immediate / Rolling
Openings
9 positions
Type
Full-time
Category
Machine Learning
About the Internship
Anand Rathi has an open Scikit-learn Modelling Intern position in Faridabad for motivated freshers and final-year students. You will work on live classical machine learning projects and finish with something you can genuinely talk about in interviews.
About the role
As a Scikit-learn Modelling…
About Anand Rathi
Anand Rathi offers a mentor-led Scikit-learn Modelling Intern in Faridabad with live project work in machine learning, a stipend of ₹17,000/month and a Pre-Placement Offer opportunity for strong performers.
See all Anand Rathiinternships →Faridabad, HaryanaVerified employer9 openings
Apply to Anand Rathi →Skills Required
Scikit-learnPythonPandasRegression & ClassificationCross-ValidationHyperparameter TuningFeature SelectionModel MetricsStatisticsMatplotlib
Who Can Apply
- Final-year students and recent graduates from B.E./B.Tech (any branch), BCA/MCA or B.Sc/M.Sc (Statistics / Mathematics / Computer Science) who are based in or willing to work from Faridabad. You should be keen to learn Scikit-learn, Python, Pandas 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
Live project experienceExposure to professional tools and workflowsPre-Placement Offer (PPO) opportunityFlexible working hoursNetworking with senior professionalsDirect access to the team that owns the data you work on
Interview & Selection Process
4 rounds — typical selection flow for this role:
- 1Application screening & resume shortlisting by the talent team
- 2Practical assignment or case study with a short walkthrough
- 3Discussion with the hiring manager on the role and your fit
- 4HR discussion — stipend, start date, expectations and offer
₹17,000/month
Stipend · 3 months
Openings9 positions
Applicants0 applied
ModeIn Office
CategoryMachine Learning
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