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Icertis logo — Icertis Text Analytics Intern in Pune, Maharashtra
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Text Analytics Intern

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Location

Pune, Maharashtra

Work Mode

Hybrid

Duration

2 months

Stipend

₹29,000/mo

Start Date

Immediate / Rolling

Openings

14 positions

Type

Full-time

Category

Data Science

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About the Internship

Join Icertis in Pune as a Text Analytics Intern. This entry-level internship is designed for students and recent graduates who learn best by building, shipping and getting real feedback on text and unstructured data analytics work. About the role As a Text Analytics Intern at Icertis, your core…

About Icertis

Icertis offers a mentor-led Text Analytics Intern in Pune with live project work in data science, a stipend of ₹29,000/month and a Pre-Placement Offer opportunity for strong performers.
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Pune, MaharashtraVerified employer14 openings
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Skills Required

PythonNatural Language Processing (NLP)Sentiment AnalysisTopic ModellingText PreprocessingspaCy / NLTKSQLData VisualisationSurvey & Review DataInsight Communication

Who Can Apply

  • Final-year students and recent graduates from B.E./B.Tech, MCA, B.Sc/M.Sc (Statistics / CS) or M.A. (Linguistics) with technical skills who are based in or willing to work from Pune. You should be keen to learn Python, Natural Language Processing (NLP), Sentiment 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

Flexible working hoursNetworking with senior professionalsInternship CertificateLetter of RecommendationMentorship from a named mentor

Interview & Selection Process

4 rounds — typical selection flow for this role:

  1. 1Application screening & resume shortlisting by the talent team
  2. 2Technical interview on fundamentals and your projects
  3. 3Practical assignment or case study with a short walkthrough
  4. 4HR discussion — stipend, start date, expectations and offer
29,000/month

Stipend · 2 months

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Openings14 positions
Applicants0 applied
ModeHybrid
CategoryData Science
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