Product Data Analyst

Remitly

Seattle, WA, USA

Full time

Apr 15

This job is no longer accepting applications.

About the Role:

The North America Product team at Remitly is creating an outstanding, seamless, cross-channel customer experience from the first time a customer on-boards to the moments they transact securely. As a Product Analyst on this team, you will work with a team of product managers, engineers, and UX designers to drive product improvements for our customers. You will propose data-driven hypotheses to improve our customer experience as well as design and analyze A/B tests. The quantitative insights you bring will have an out-sized impact on the business. You will report directly to our Director of Product Analytics.

What You'll Do:

  • Develop insightful metrics that cut beyond the surface level to product adoption, retention, and engagement.
  • Analyze user behavior to identify patterns, uncover opportunities, and build a shared understanding of how our users are engaging with the platform.
  • Promote insight generation through advanced business analytics to improve our post-purchase customer journeys.
  • Partner with Product Management to build a prioritization framework that captures relevant tradeoffs for the team including setting goals and evaluating potential opportunities.
  • Ensure data-driven decision-making by aggregating data across multiple sources and compiling it into a digestible and actionable format
  • Explain the methods behind your analyses and validate your results. Once you have data to support your ideas, you're willing to advocate for and move your recommendations forward.

You have:

  • Bachelor's degree in a technical, business, or quantitative field (Computer Science, Engineering, Statistics, or related field).
  • Minimum two years of relevant experience in a product or customer analytics role.
  • Experience focused on feature and usage metrics, customer segmentation, and developing user archetypes and their usage patterns
  • Experience uncovering insights to form hypothesis, designing product experiments, evaluating results and making recommendations
  • Experience with technical skills (e.g. SQL, R, Python) and data visualization tools (e.g. Tableau)


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