Product Intern

0 years

0 Lacs

Posted:1 week ago| Platform: Linkedin logo

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On-site

Job Type

Internship

Job Description

Product Intern – Data Science x Product Ops

We’re on the hunt for curious, hands-on folks who thrive on solving real-world problems. You’ll start by getting your hands dirty — annotating images, clustering outlets, tagging data — the gritty work that powers our ML systems and builds domain depth. As you ramp up, you'll move into more complex tasks: running experiments, writing logic, and shaping how our next-gen, ML-powered CPG tools behave. If you're analytical, adaptable, and excited about working at the intersection of data, tech, and product — we want to hear from you.

For one in the Seat:

Responsibilities:

  • Analyze product and user behavior data to identify trends, gaps, and improvement opportunities
  • Support product managers in performance tracking, product readiness, and user research.
  • Execute critical groundwork like image annotation, outlet clustering, data tagging, and documentation
  • Contribute to product experiments, testing, and model input/output validation
  • Use Excel and internal tools to build dashboards, reports, and performance views
  • Run analyses on internal platforms for insights and client-facing deliverables
  • Leverage your data science foundation (Python, pandas, ML basics) to support model design and tooling
  • Collaborate across product, design, engineering, and business teams to bring clarity to decision making.

Who we're looking for:

  • Strong problem-solving and analytical mindset
  • Proficiency in MS Excel (pivot tables, formulas, charts, VLOOKUP) the usual
  • Exposure to Python, pandas, Jupyter notebooks, or ML concepts — you don’t need to be a wizard, but you should be hungry to learn
  • Comfortable with hands-on grunt work and iterative workflows
  • Curiosity about how products are built, scaled, and improved through data
  • Team player who communicates well and thrives in slightly chaotic but high-energy setups.
  • Bonus: Prior exposure to SaaS, CPG, or product management

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