Receipt Bank is a rapidly scaling FinTech business on a mission to disrupt the world of accounting and bookkeeping. Our products allow 360,000+ SMEs and their accounting partners automate bookkeeping processes through our award-winning Machine Learning. Founded in 2010, we have achieved near 100% growth year-on-year, opened offices globally and won several awards along the way. January 2020 saw us close $73m in our Series C, and we are looking to expand our machine learning offering by 10x.

Role Summary

We are looking for someone who has some solid early exposure to Machine Learning, Neural Networks and Deep Learning. You’ll likely be a budding Data Scientist with 1+ year’s experience working in a ML-driven environment, but keen to transition into a Product role.

Or you’ll be a Product Manager with some early experience working with ML, Deep Learning technology.

Either way, you’ll be integral to working on our data extraction and optimisation workstream, leading our efforts in Machine Learning, Computer Vision, Natural Language Processing and more to find and drive data efficiencies across the 100m+ of data documents we capture.

Our product development life cycle is built from our unrelenting focus on personalising our end-user experience, using the extensive data insights and customer touch points we have. This role is focused on the core of our offering; it requires someone who has industry foresight as well as the analytical capability to drive the product changes needed


Receipt Bank


To research world class automative features (30%)
Research and understand users and their needs
Analyse the data we already hold on our users and find new data sources
Define and measure success
Understand our competitors and research their features
Have an awareness of regional preferences in bookkeeping
Research how Data Extraction will operate all RBG markets
Manage the product development of Data Extraction (70%)
Define and Lead OKRs for Data Extraction
Develop and maintain the roadmap for Data Extraction
Partner with all stakeholders to ensure collective buy-in
Monitor and manage the development of new features
Host regular firesides in global offices to inform them of progress and achievements
Maintain regular updates via internal channels on performance or new features
Use Machine Learning techniques to aid development and scalability
Work closely with UX and UI Teams to find solutions

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