We're looking for a Product Data Scientist excited to help build the bank of the future. You'll have the opportunity to super charge our user engagement in 2021 and help us to build a bank that customers truly love.
At Monzo, we're building a bank that is fair, transparent and a delight to use. We’re growing extremely fast and have over four and half million customers in the UK, with over 100,000 new people joining every month. We’ve built a product that people love and more than 80% of our growth comes from word of mouth and referrals.
Our Product Analytics team's mission is to
Enable Monzo to Make Better Decisions, Faster
We have a strong culture of data-driven decision making across the whole company. And we're great believers in powerful, real-time analytics and empowerment of the wider business. All our data lives in one place and is super easy to use. 90% of day-to-day data-driven decisions are covered by self-serve analytics through Looker which gives data scientists the head space to focus on more impactful business questions and analyses.
We work in cross-functional squads where every data scientist is a member of a central data discipline and fully embedded into 1 product squad alongside engineers, designers, marketers, product managers etc.
Autonomy. We believe that people reach their full potential when you can remove all the operational obstacles out of their way and let them run with their ideas. This comes together with a strong sense of ownership for your projects. At Monzo, you will get full access to our data and analytics infrastructure. When you discover something interesting, there is nothing stopping you from exploring and implementing your coolest ideas.
Cutting-edge managed infrastructure. All our data infrastructure lives on the Google Cloud Platform, so you don't need to spend your time configuring or managing clusters, databases, etc. If you want to train a Machine Learning model faster, just spin up a compute engine instances and submit a job from your local machine, no DevOps skills required.
Automation. We aim to automate as much as we can, so that every person in the team can focus on the things that humans do best. As with all data science work, there’s some analysis and reporting, and as much as possible we encourage self-serve access to our data through Looker.
We can help you relocate to London & we can sponsor visas.
We offer share options and competitive salaries based on skills and experience.
Our interview process is normally a phone interview, a take home task and call to discuss it, and 2-3 hours of onsite interviews. We promise not to ask you any brain teasers or trick questions.
Diversity and inclusion is a priority for us – if we want to solve problems for people around the world, our team has to represent our customers. So we need to attract the best talent and create an environment that supports and includes them. You can read more about diversity and inclusion on our blog.
If you prefer to work part-time, from home or as a job-share, we'll make this happen whenever we can - whether this is to help you meet other commitments or strike a great work-life balance.
Questions about this role? Head over to our careers page to read our FAQs (www.monzo.com/careers)
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