Product data and insights analyst (fresher)

0 years

0 Lacs

Posted:1 month ago| Platform: Linkedin logo

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Work Mode

On-site

Job Type

Full Time

Job Description

About the Role

entry-level team member

analytical, detail-oriented, and excited about climate tech


What You’ll Do

  • Prepare

    client-specific demo datasets

    that reflect realistic scenarios
  • Build and maintain

    benchmarking datasets

    (e.g., sectoral emissions, GHG factors)
  • Create and improve

    Excel/Google Sheets templates

    used in the product
  • Work with the product team to improve demo usability and ease of data entry
  • Support custom requests for dashboards, mock data, or tool enhancements
  • Research ESG-related data sources and help translate them into usable product insights


What We’re Looking For

  • Freshers and recent grads welcome

    — especially from backgrounds in engineering, economics, environmental sciences, or business
  • Strong skills in

    Excel/Google Sheets

    (basic formulas, lookups, tables)
  • Comfortable working with numbers, data, and structure
  • Interest in

    sustainability, ESG, or climate tech

  • Attention to detail, willingness to learn, and proactive problem-solving
  • Bonus: Familiarity with PowerPoint or Canva for client-facing materials


Why Join Us?

  • Work in a

    fast-growing sustainability tech company

  • Learn from cross-functional teams across product, GTM, and sustainability
  • Build a strong foundation in ESG data, carbon reporting, and product thinking
  • Be part of a mission-driven team tackling real climate challenges


PREREQUISITE EXERCISE

As a pre-requisite, pls submit this exercise to divya.sukumar@karbonwise.com


Imagine KarbonWise is building a benchmarking dataset for energy intensity (kWh/m²/year) in commercial real estate.

  • List

    3 segments

    you would want to include (e.g., malls, offices, warehouses)
  • What kind of

    data points

    would you collect for each?
  • Suggest 2–3

    sources

    or ways you might find this data (even if not exact)
  • If you had to make assumptions to fill gaps, how would you document them?





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