We're looking for a curious, adaptable Senior Data Scientist to join the Data & Customer Operations teams at Monzo!
You'll have the chance to analyse all aspects of our customer support operations and help the teams scale how we work to support millions of customers.
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 everyday 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.
The Data & Customer Operations teams
The data team's mission is to
Enable Monzo to Make Better Decisions, Faster
This mission encompasses three major areas of work: (1) product analytics, to help teams understand our customers and improve our app (2) domain analytics, to support teams who are working in specific banking disciplines (e.g., lending, operations, finance, and financial crime), and (3) machine learning, where we design and build system that automate decisions across Monzo. While we take a flexible approach and frequently help each other across these areas, we each have one domain as our primary focus. We work in cross-functional squads, so every data scientist is a member of the central data team as well as fully embedded into another team alongside engineers, designers, product managers etc.
For this role, we are looking for a Data Scientist/Analyst who will focus on customer operations analytics. You’ll be working at the intersection of the Data & Customer Operations teams.
The Customer Operations team look after the tasks within Monzo that scale with customers. They're a crucial link between Monzo and our customers. The Customer Operations team is comprised of multiple product squads, a planning team, and an incubator team. All of these teams work to make sure we can support Monzo's explosive growth through running a variety of optimisation projects for Customer Operations.
The Customer Operations team are solving some of the most exciting problems in Monzo. There are lots of unsolved, hard problems where data plays a key part but you will also need to think deeply about people, product and process when solving these problems.
A few examples of questions and challenges:
- How can we measure and optimise a system that handles thousands of queries a week? What product improvements can we make? How can we understand if these are impactful?
- What are our customers contacting us about & when/how can we automate the answer to their question? (partnering with the machine learning and software engineering teams)
- How can we drive efficiency by 20% for our customer operations? What is the best way to measure efficiency?
- What sets the most effective COps (the lovely customer support people who chat to our customers) apart?
- What is a good customer experience? How can we measure this? How can we optimise for this?
- How do we balance (i) providing an amazing customer experience (ii) cultivating a positive and motivating culture for our customer support agents and (iii) being the most efficient and flexible operations team in the industry.
- How can we automate our processes in a way that will allow us to scale to 1 billion customers and thousands of COps?
You will help us make data-driven decisions and shape the direction of this exciting and evolving part of the Monzo business. We’re looking for someone who cares deeply about understanding our business and customers, who can communicate their findings clearly to business partners and can drive actions on top of insights.
What’s special about data at Monzo?
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.
You should apply if:
- What we’re doing here at Monzo excites you!
- You want to have a real positive impact on the company, product, users and your colleagues
- You pro-actively identify issues, and enjoy tackling them and coming up with solutions
- You’re comfortable getting hands-on and taking a step back to think strategically
- You're a team player whom your colleagues can rely on
- You have solid grounding in SQL and preferably Python
- You are happiest exploring data, making discoveries and understanding their implications
- You can manage multiple stakeholders with competing priorities
We can help you relocate to London & we can sponsor visas.
We offer share options and competitive salaries based on skills and experience, which could be anywhere between £49,000 - £80,000 per year.
We're usually always hiring for Data Scientist, so there's no closing date for this job.
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)