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Senior Data Scientist, Operations 658 views

They’re looking for a curious, adaptable Data Scientist to join the Data & Customer Operations teams at Monzo!

You’ll have the chance to analyze all aspects of their customer support operations and help the teams scale how they work to support millions of customers.

They have a strong culture of data-driven decision making across the whole company. And they’re great believers in powerful, real-time analytics and empowerment of the wider business. All their 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 headspace 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 their customers and improve their 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 they design and build a system that automates decisions across Monzo. While they take a flexible approach and frequently help each other across these areas, they each have one domain as their primary focus. They work in cross-functional squads, so every data scientist is a member of the central data team as well as fully embedded into an area such as operations or product squads.

For this role, they 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 looks after the tasks within Monzo that scale with customers. They’re a crucial link between Monzo and its customers. Customer Operations spans multiple product squads, a planning team, an incubator team, and almost 1,000 passionate COps (that’s what we call their agents). All of these teams work to make sure they can support Monzo’s explosive growth by running a variety of optimization projects for Customer Operations.

The role

The Customer Operations team is 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 do they balance (i) providing an amazing customer experience (ii) cultivating a positive and motivating culture for their customer support agents and (iii) being the most efficient and flexible operations team in the industry?
    • How can they automate their processes in a way that will allow them to scale to 1 billion customers and thousands of COps?
    • How can they measure and optimize a system that handles thousands of queries a week? What product improvements can they make? How can they understand if these are impactful?
    • What are their customers contacting them about & when/how can they automate the answer to their question? (partnering with the machine learning and software engineering teams)
    • How can they drive efficiency by 20% for their customer operations? What is the best way to measure efficiency?
    • What sets the most effective COps (the lovely customer support people who chat to their customers) apart?
    • What is good customer experience? How can they measure this? How can they optimize for this?

You will help them make data-driven decisions and shape the direction of this exciting and evolving part of the Monzo business. They’re looking for someone who cares deeply about understanding their 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. They 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 their 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 their 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. They aim to automate as much as they 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 they encourage self-serve access to their data through Looker.

You Should Apply If

    • What they’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 a 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


They can help you relocate to London & they can sponsor visas.

They offer share options and competitive salaries based on skills and experience, which could be anywhere between £49,000 – £80,000 per year.

They’re usually always hiring for Data Scientist, so there’s no closing date for this job.

Their interview process is normally a phone interview, a take-home task and call to discuss it, and 2-3 hours of onsite interviews. They promise not to ask you any brain teasers or trick questions.

Diversity and inclusion is a priority for them – if they want to solve problems for people around the world, their team has to represent their customers. So they need to attract the best talent and create an environment that supports and includes them. You can read more about diversity and inclusion on their blog.
If you prefer to work part-time, from home, or as a job-share, they’ll make this happen whenever they can – whether this is to help you meet other commitments or strike a great work-life balance.

Questions about this role? Head over to their careers page to read our FAQs (

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