Ultraviolette Automotive
Fraud Detection ML Intern
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Skills you'll use
What you'll do
- Work on catching fraudulent behaviour without blocking legitimate customers alongside the core team
- Apply Anomaly Detection, Python, Imbalanced Data Techniques, Feature Engineering 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, MCA, M.Sc (Statistics / Data Science) or MBA (Analytics)
- Graduating batch 2026, 2027 or 2028 — final-year students and recent graduates welcome
- 60% / 6.0 CGPA and above preferred; strong project work is considered alongside academics
- Working knowledge of Anomaly Detection, Python, Imbalanced Data Techniques (or a genuine willingness to learn them)
- Exposure to Feature Engineering, Scikit-Learn, SQL is an advantage
- Clear written and verbal communication in English, and care with detail in your work
- No prior work experience required — this is a fresher-friendly internship
- Based in Thane, Maharashtra or willing to work from there for the internship period
Perks & benefits
Interview & selection process
2 rounds — typical selection flow for this role:
- 1Application screening & resume shortlisting by the talent team
- 2Discussion with the hiring manager on the role and your fit
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