We're looking for a curious, adaptable Data Scientist to join the Operations Planning team at Monzo!
You’ll have the chance to analyse, build, and optimise World Class schedules for our customer support agents, allowing us to meet incoming customer demand, and help us scale to support millions of customers.
The Data and Ops-planning 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 who will be embedded in the Workforce planning squad.
The Workforce Planning squad enables customer support through a variety of workforce planning tasks. These include determining customer support agent headcount for the next 24 months, forecasting multi-channel inbound customer support requests, optimising customer support agents’ schedules, and many automations of workforce-related tasks. The team is crucial in supporting a customer support workforce that both meets customer demand and is a joy to work in.
You’ll help us with the following questions and challenges:
- Build and curate a schedule assignment algorithm that enables a multi-pass optimisation approach, considering demand matching and customer operations team members’ working preferences
- Developing mathematical models to optimise our customer support scheduling
- Forecasting inbound requests
- Developing alerting systems that warn us when we expect queues to worsen
- Automating our processes in a way that will allow us to scale to 1 billion customers and thousands of customer support agents
Along with other data scientists and the head of workforce planning, you’ll work to deliver a cutting-edge workforce planning solution that takes into account inbound demand and agents’ shift preferences.
You’ll also work closely with software engineers and product managers in the internal product team to architect solutions to solve common workforce planning problems. These include deploying your mathematical models, re-optimising to handle real time fluctuations in customer demand, deploying microservices to handle automatic shift change requests etc.
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 a solid grounding in SQL and Python, and are comfortable using them every day
- You have experience or are willing to learn workforce scheduling optimisation techniques.
- (optional) You have experience with linear/integer programming and mathematical solvers
- (optional) You have experience doing optimisation in a mathematical programming language
This role is based at our office in London.
We care deeply about inclusive working practices and diverse teams. If you’d prefer to work part-time or as a job-share, we’ll facilitate this wherever we can - whether to help you meet other commitments or to help you strike a great work-life balance.
Our interview process consists of a 30-minute phone interview, a take-home test, and a half-day on-site interview. We promise not to ask you any brain teasers or trick questions!