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Open nowPosted 722 days ago

Associate, Product and Data

Newslaundry1 open role

Where
Delhi, India
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Your applicationOpen nowAssociate, Product and DataNewslaundry · Delhi, India

  1. YouYes, apply to this one.

  2. CV RocketCV written for this posting.

  3. 25 readersRecruiter, hiring manager, skeptic. Round after round.

  4. CV RocketApplied on Newslaundry's own form.

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The clock on this job

Early applications get read.

11.5% of postings close within 7 days. Measured by our own scanner across the market.

Share of postings closed within
  1. 2.0%1 day
  2. 4.3%3 days
  3. 11.5%7 days
  4. 18.1%14 days
  5. 35.6%30 days
  6. 44.6%60 days
This job: posted 722 days ago

The posting

At Newslaundry, we take pride in delivering a news product that readers find value in and pay for. Our community of subscribers from across the world turn to us for an ad-free, subscriber-first experience that is embedded in our product DNA. User experience and data-driven decisions are key to that value proposition. As part of the product and revenue team, you will analyse user behaviour data, track performance across products and verticals for actionable insights, and lead all our efforts that require data analysis. Apply if you’re someone who loves Excel, dashboards and understands the value of data analysis in building a news product. Responsibilities: Gather insights that shape product development and lead to a better subscriber experience Lead all data aznd performance analysis Requirements What you should have: Have strong analytical and number-crunching skills Knack for breaking down complex datasets and analytics into digestible, actionable insights Proficiency in MS Excel, Google Sheets, Google Analytics and Google Data Studio Prior experience with any of the product analytics tools, such as Firebase, Mix Panel At least one of work experience in a data or analytics role Bonus points if you have: Prior experience in working with any the BI platforms, such as Metabase, After Glow, Power BI

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    The review screen in CV Rocket: how each CV was read, round by round.

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