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Myntra logo — Myntra Time Series Forecasting Intern in Bengaluru, Karnataka
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Time Series Forecasting Intern

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Location

Bengaluru, Karnataka

Work Mode

Hybrid

Duration

2 months

Stipend

₹34,000/mo

Start Date

Immediate / Rolling

Openings

11 positions

Type

Full-time

Category

Machine Learning

Apply Now — ₹34,000/moApply on Company Website ↗

About the Internship

Myntra is hiring a Time Series Forecasting Intern in Bengaluru — a hands-on, mentor-led internship built for students and 2026 freshers who want real exposure to time-series forecasting rather than a certificate-only programme. About the role As a Time Series Forecasting Intern at Myntra, your…

About Myntra

Myntra offers a mentor-led Time Series Forecasting Intern in Bengaluru with live project work in machine learning, a stipend of ₹34,000/month and a Pre-Placement Offer opportunity for strong performers.
Bengaluru, KarnatakaVerified employer11 openings
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Skills Required

Time-Series AnalysisARIMA & ProphetPythonSeasonality & Trend DecompositionForecast Accuracy (MAPE / RMSE)Feature EngineeringPandasStatistical TestingBacktestingData Visualisation

Who Can Apply

  • Final-year students and recent graduates from B.E./B.Tech, B.Sc/M.Sc (Statistics / Mathematics / Economics) or MCA who are based in or willing to work from Bengaluru. You should be keen to learn Time-Series Analysis, ARIMA & Prophet, Python 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

Internship CertificateLetter of RecommendationMentorship from a named mentorLive project experienceExposure to professional tools and workflows

Interview & Selection Process

3 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. 3HR discussion — stipend, start date, expectations and offer
34,000/month

Stipend · 2 months

Apply Now →
Openings11 positions
Applicants0 applied
ModeHybrid
CategoryMachine Learning
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