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Data Scientist, Operations

Entry-level at Monzo Bank

Data Scientist, Operations

Entry-level at Monzo Bank

  • LocationLondon, UK
  • Position levelEntry-level
  • Job period iconFull-time employment
  • Application deadline iconApply by 28 Dec, 2018
  • Application deadline iconPosted on 29 Oct, 2018
  • Start date iconStart date:
  • Visa iconVisa Sponsor
  • CompetitiveCompetitive
We're looking for a curious, adaptable 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 & Scalers 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, and Scalers teams.
The Customer Operations team look after the tasks within Monzo that scale with customers. They're a crucial link between Monzo and our users. They help people manage their money, solve their problems, and listen to their feedback on our features. The Scalers team makes sure we can support Monzo’s explosive growth through running a variety of optimisation projects for Customer Operations.

The role

You’ll help us with the following questions and challenges:
  • What our customers are contacting us about and why
  • How impactful was the last product release in terms of customer query volume and what we can do better
  • What sets the most effective COps (the lovely customer support people who chat to our customers) apart
  • How are we doing with respect to hitting our service targets (e.g. waiting time on a call) and how can we empower teams to prioritise their work better
  • Which features we should develop in our internal tooling next, based on analytics and performance metrics
  • How can we automate our processes in a way that will allow us to scale to 1 billion customers and thousands of COps
You’ll interface with people across Operations, being their primary contact on all things data, from individual performance dashboards to analysing long term trends.
You’ll also work closely with engineers in the Scalers team to ensure that we are collecting all the necessary data that we will need for future analyses. You will help us make data-driven decisions and shape the direction of internal product development, as well as how we can further reduce customer contact in the future.
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 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

Logistics

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!

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Job location

38 Finsbury Square, London, UK

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