Location
GIFT City, Gandhinagar, Gujarat
Work Mode
In Office
Duration
3 months
Stipend
₹22,000/mo
Start Date
Immediate / Rolling
Openings
11 positions
Type
Full-time
Category
Machine Learning
About the Internship
Nestle India has an open Fraud Detection ML Intern position in GIFT City, Gandhinagar for motivated freshers and final-year students. You will work on live fraud and anomaly detection projects and finish with something you can genuinely talk about in interviews.
About the role
As a Fraud Detection…
About Nestle India
Nestle India offers a mentor-led Fraud Detection ML Intern in GIFT City, Gandhinagar with live project work in machine learning, a stipend of ₹22,000/month and a Pre-Placement Offer opportunity for strong performers.
See all Nestle Indiainternships →GIFT City, Gandhinagar, GujaratVerified employer11 openings
Apply to Nestle India →Skills Required
Anomaly DetectionPythonImbalanced Data TechniquesFeature EngineeringScikit-LearnSQLPrecision-Recall TradeoffsRule + Model HybridsModel ExplainabilityDomain Investigation
Who Can Apply
- Final-year students and recent graduates from B.E./B.Tech, MCA, M.Sc (Statistics / Data Science) or MBA (Analytics) who are based in or willing to work from GIFT City, Gandhinagar. You should be keen to learn Anomaly Detection, Python, Imbalanced Data Techniques 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
Networking with senior professionalsInternship CertificateLetter of RecommendationMentorship from a named mentorLive project experience
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
₹22,000/month
Stipend · 3 months
Openings11 positions
Applicants0 applied
ModeIn Office
CategoryMachine Learning
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