Location
Gandhinagar, Gujarat
Work Mode
In Office
Duration
2 months
Stipend
₹26,000/mo
Start Date
Immediate / Rolling
Openings
7 positions
Type
Full-time
Category
Machine Learning
About the Internship
Tata Projects has an open Time Series Forecasting Intern position in Gandhinagar for motivated freshers and final-year students. You will work on live time series analysis and forecasting projects and finish with something you can genuinely talk about in interviews.
About the role
As a Time Series…
About Tata Projects
Tata Projects offers a mentor-led Time Series Forecasting Intern in Gandhinagar with live project work in machine learning, a stipend of ₹26,000/month and a Pre-Placement Offer opportunity for strong performers.
See all Tata Projectsinternships →Gandhinagar, GujaratVerified employer7 openings
Apply to Tata Projects →Skills Required
Time Series AnalysisARIMA & ProphetSeasonalityBacktestingPythonPandasStatisticsFeature EngineeringForecast Accuracy (MAPE)Visualisation
Who Can Apply
- Final-year students and recent graduates from B.E./B.Tech (any branch), MCA, M.Sc (Statistics / Mathematics / Economics) or equivalent who are based in or willing to work from Gandhinagar. You should be keen to learn Time Series Analysis, ARIMA & Prophet, Seasonality 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 experienceStructured onboarding and a formal mentor at a large, established employer
Interview & Selection Process
4 rounds — typical selection flow for this role:
- 1Application screening & resume shortlisting by the talent team
- 2Online aptitude / domain assessment
- 3Technical interview on fundamentals and your projects
- 4HR discussion — stipend, start date, expectations and offer
₹26,000/month
Stipend · 2 months
Openings7 positions
Applicants0 applied
ModeIn Office
CategoryMachine Learning
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