Job description

We are looking for data geeks who live and breathe data and see them like Lego pieces that create a strong foundation on any product possibilities! We want someone who wants to build advanced and technically sophisticated data products that will power Pace’s various financial products.


Most importantly, we want you to be passionate about what you do. We want you to be flexible enough to learn fast and work through details, but also have great resolve in solving difficult problems and being ultra reliable. But above everything we want you to build products with us, as a team of great technical talent who share experiences, and do great work together.


So, if you’re not afraid of these huge challenges, you’re the person we’re looking for, and we’ll see you at Pace very soon!


Responsibilities:

  • Partner with product and engineering to aid in the development of a world class financial products across our mobile and web products
  • Develop a deep understanding of Pace’s products and aid in the creation of Key Performance Indicators (KPIs) that can be measured to define success
  • Perform and present analysis aimed at understanding both potential members and current members (e.g., cohort analysis, funnel analysis, segmentation analysis, etc.)
  • Collaborate with product managers, data engineers, researchers, key stakeholders to solve various business problems
  • Provide strategic analytical support to our internal products teams, helping to empower Pace employees to do their jobs in the most efficient way possible
  • Contribute to and participate in continuous learning with the team through demos and peer reviews
  • Take initiative to explore data independently to generate insights and/or data products that will help the company move forward

Requirements:

  • 3+ years experience in a product data science or similar role
  • Experience working on an e-commerce platform or financial technology products
  • Experience working with product, design, and engineering leads on digital products
  • Proficient in SQL and at least one scripting language (Python preferred)
  • Experience with hypothesis testing, experimental design, and a strong understanding of statistics
  • Experience with Segment, Snowflake, Amplitude, Looker, Tableau or comparable platforms
  • Strong data visualization skills and ability to present insights from analysis
  • Highly collaborative and able to communicate effectively, both verbally and in writing
  • BA/BS or M.S degree in a quantitative field (e.g., statistics or mathematics), or equivalent practical experience

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