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INDmoney logo — INDmoney Python for Data Engg Intern in Visakhapatnam, Andhra Pradesh
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Python for Data Engg Intern

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Location

Visakhapatnam, Andhra Pradesh

Work Mode

Hybrid

Duration

2 months

Stipend

₹21,000/mo

Start Date

Immediate / Rolling

Openings

3 positions

Type

Full-time

Category

Data Science

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About the Internship

Join INDmoney in Visakhapatnam as a Python for Data Engg Intern. This entry-level internship is designed for students and recent graduates who learn best by building, shipping and getting real feedback on Python data engineering work. About the role As a Python for Data Engg Intern at INDmoney…

About INDmoney

INDmoney offers a mentor-led Python for Data Engg Intern in Visakhapatnam with live project work in data science, a stipend of ₹21,000/month and a Pre-Placement Offer opportunity for strong performers.
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Visakhapatnam, Andhra PradeshVerified employer3 openings
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Skills Required

PythonPandasNumPySQLAlchemyREST APIsFile Formats (CSV/Parquet)Error HandlingLoggingUnit TestingGit

Who Can Apply

  • Final-year students and recent graduates from B.E./B.Tech (CSE/IT), BCA/MCA or B.Sc/M.Sc (Computer Science / Statistics) who are based in or willing to work from Visakhapatnam. You should be keen to learn Python, Pandas, NumPy 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

Flexible working hoursNetworking with senior professionalsInternship CertificateLetter of RecommendationMentorship from a named mentorDirect access to the team that owns the data you work on

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
21,000/month

Stipend · 2 months

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Openings3 positions
Applicants0 applied
ModeHybrid
CategoryData Science
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