About us:
Luno is the crypto investment app you can rely on, enabling you to buy, store and explore crypto securely. We're committed to putting the power of cryptocurrency in everyone's hands sensibly and responsibly.
Since 2013, we've helped millions of people around the world invest safely in crypto. We do this by cutting through the hype and supporting customers at every step of the way. All products and cryptocurrencies on our platform must first meet stringent legal, risk and technical security standards.
Transparency is key for us. Luno stores all crypto on a 1:1 basis and we have rigorous processes in place so you can be confident your investment is secure. We're available in more than 40 countries around the world and we work closely with respective regulators in all of these markets to be fully compliant, as we believe this is the best way to help everyone, everywhere, invest safely.
About the team:
The Data community at Luno, comprising Data Engineers, Scientists and Analysts, uncovers valuable insights from the vast amounts of data we gather from our customers and platform. These insights are crucial for guiding our product development and business strategy.
As a Product Data Scientist joining Luno, you would be part of the Product Analytics team providing high quality insights into our product through experimentation and advanced analytics.
Our current technology stack includes Databricks, Thoughtspot, Amplitude and Segment.
The role in a nutshell:
As we accelerate on our mission to put crypto in everyone's hands, your role is to use data and insights to drive better product decisions and influence the Luno product strategy. This will involve collaborating with cross-functional teams to find, size, prioritise, evaluate and iterate on problems and opportunities to enhance our product.
This is a hands-on product analytics role focused on experimentation, customer behaviour and data-informed decision-making. While there may be opportunities to apply modelling or machine learning techniques for specific use cases, this is not a production ML-focused role.
Your mission will be:
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