Lead Data Scientist, Operations
We’re here to make money work for everyone and we're doing things differently. For too long, banking has been obtuse, complex and opaque.
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.
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 giving data scientists the head space to focus on more impactful business questions and analyses.Our data science mission is to Enable Monzo to Make Better Decisions, Faster.
About our Data Team:
We're looking for a Data Scientist for our Operations Collective, excited to help build the bank of the future. You'll have the opportunity to work on an area that is the heart of how we work with our customers’ problems - and is full of data challenges: product and journey experiments, forecasting supply and demand, operational research, all to understand the biggest opportunities to improve how we serve our customers - matching customer problems to people who can solve them in the best way.
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. All of our infrastructure is designed so that we can have really high data quality, and spend most of our time using that data to support business decisions.
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.
- Work in product teams with engineers, designer, product, user researchers to measure things that matter; design and analyse A/B experiments to keep improving everything we do; offer actionable recommendations to stakeholders
- Apply your expertise in quantitative analysis, data mining, forecasting and machine learning / operational research, to see beyond the numbers and understand how our users interact with our products and how those insights can inform our product and operations strategy
- Optimise our planning, scheduling and assignment of Monzo customer operations. Create forecasts of demand (customer problems) and supply (operations agents) to drive our hiring pipelines based on customer needs and skills. Coupled this with matching algorithms we to optimise our operations strategy to have right people solving the right customer problems at the right time
You should apply if:
- What we’re doing here at Monzo excites you! You're impact driven and eager to have a real positive impact on the company, product, users and very importantly your colleagues as well
- You're operationally and commercially minded, can put numbers into business perspective
- You’re as comfortable getting hands-on as taking a step back and thinking strategically
- You have a self-starter mindset; you proactively identify issues and opportunities and tackle them without being told to do so
- You're a team player whom your colleagues can rely on
- You have solid grounding in SQL and preferably Python
- You have experience in either conducting large scale A/B experiments, operational research algorithms, or complex forecasts
The interview process:
Our interview process involves 4 main stages:
- Recruiter Call
- Initial Call
- Final Interview
- Business Fit/Collaboration
- Case Study
- Technical Interview
- Final Decision
Our average process takes around 2-3 weeks but we will always work around your availability. You will have the chance to speak to our recruitment team at various points during your process but if you do have any specific questions ahead of this please contact us on *hiring email*
One of our recruiters has written a blog on the process, for extra details, hints and tips please see Data Hiring at Monzo
What’s in it for you:
💰 £100,000 - £140,000 base salary + plus stock options
✈️We can help you relocate to the UK
✅We can sponsor visas.
📍This role can be based in our London office, but we're open to distributed working within the UK (with ad hoc meetings in London).
⏰We offer flexible working hours and trust you to work enough hours to do your job well, at times that suit you and your team.
📚Learning budget of £1,000 a year for books, training courses and conferences
➕And much more, see our full list of benefits here
If you prefer to work part-time, we'll make this happen whenever we can - whether this is to help you meet other commitments or strike a great work-life balance.
Equal Opportunity Statement
We are actively creating an equitable environment for every Monzonaut to thrive.
Diversity and inclusion are a priority for us and we are making sure we have lots of support for all of our people to grow at Monzo. At Monzo, embracing diversity in all of its forms and fostering an inclusive environment for all people to do the best work of their lives with us. This is integral to our mission of making money work for everyone. You can read more in our blog, 2022 Diversity and Inclusion Report and 2022 Gender Pay Gap Report.
We’re an equal opportunity employer. All applicants will be considered for employment without attention to age, ethnicity, religion, sex, sexual orientation, gender identity, family or parental status, national origin, or veteran, neurodiversity or disability status.