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Navi logo — Navi Growth Data Science Intern in Faridabad, Haryana
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Growth Data Science Intern

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Location

Faridabad, Haryana

Work Mode

Hybrid

Duration

6 months

Stipend

₹17,000/mo

Start Date

Immediate / Rolling

Openings

13 positions

Type

Full-time

Category

Data Science

Apply Now — ₹17,000/moApply on Company Website ↗

About the Internship

Join Navi in Faridabad as a Growth Data Science Intern. This entry-level internship is designed for students and recent graduates who learn best by building, shipping and getting real feedback on growth and product data science work. About the role As a Growth Data Science Intern at Navi, your…

About Navi

Navi offers a mentor-led Growth Data Science Intern in Faridabad with live project work in data science, a stipend of ₹17,000/month and a Pre-Placement Offer opportunity for strong performers.
Faridabad, HaryanaVerified employer13 openings
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Skills Required

SQLPythonFunnel & Cohort AnalysisA/B TestingRetention ModellingProduct AnalyticsSegmentationData VisualisationMetric DesignStorytelling

Who Can Apply

  • Final-year students and recent graduates from B.E./B.Tech, BBA/MBA, B.Sc (Statistics / Economics) or BCA/MCA who are based in or willing to work from Faridabad. You should be keen to learn SQL, Python, Funnel & Cohort Analysis 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

4 rounds — typical selection flow for this role:

  1. 1Application screening & resume shortlisting by the talent team
  2. 2Practical assignment or case study with a short walkthrough
  3. 3Discussion with the hiring manager on the role and your fit
  4. 4HR discussion — stipend, start date, expectations and offer
17,000/month

Stipend · 6 months

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Openings13 positions
Applicants0 applied
ModeHybrid
CategoryData Science
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