- Job Type: Full-Time
- Function: Data Science
- Industry: Fintech
- Post Date: 06/10/2021
- Website: monzo.com
- Company Address: 12 Epworth Street, EC2A 4DL, London, UK
About MonzoAt Monzo, we’re building a new kind of bank. One that lives on your smartphone and built for the way you live today. By solving your problems, treating you fairly and being totally transparent, we believe we can make banking better.
We're looking for a curious, adaptable Data Scientist to join our team at Monzo!
You will be responsible for partnering with stakeholders in Operations and Fincrime to develop evidence-driven solutions to important Operational and Financial Crime problems. You will apply your data expertise to surfacing key insights that will help drive decision-making, and develop data tools (where appropriate) that will improve our ability to fight financial crime and keep customers safe. You will work together with other members of the data discipline to maintain high quality, accurate data that our stakeholders can rely on.
Data at Monzo
Our Data team's mission is to
Enable Monzo to Make Better Decisions, Faster
At the core of this mission sits our data platform. We're great believers in powerful, real-time analytics and empowerment of the wider business. Every engineer at Monzo is responsible for collection of relevant analytics events from their microservices. We optimise for simplicity and re-usability – all our data lives in one place and is made available via our data warehouse in Google BigQuery. 90% of day-to-day 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.
Our technology stack
We rely heavily on the following tools and technologies (note we do not expect applicants to have prior experience of all them):
- Google Cloud Platform for all of our analytics infrastructure
- dbt and BigQuery SQL for our data modelling and warehousing
- Python for data science
- Go to write our application code
- AWS for most of our backend infrastructure
Working in a multi-disciplinary data and engineering squad, you will:
- Work closely with financial crime analysts, operations analysts, data scientists and engineers to understand the underlying business problem and propose an appropriate solution (whether involving purely engineering, purely data or both)
- Translate regulatory reporting requirements into highly accurate data models and set the strategy for how we ensure the best possible data accuracy
- Build robust data models, reports and visualisations downstream of backend services (mostly in BigQuery SQL) that support internal management information as well as governance and regulatory reporting
- Investigate and effectively work with colleagues from other disciplines to address and improve data quality
- Conduct deep dives into various Fincrime systems for fraud detection, transaction monitoring and customer risk to identify key business opportunities
- Develop and drive data solutions that improve our ability to fight financial crime and keep customers safe
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.
You should apply if
- You have strong SQL skills and are familiar with BigQuery and/or general data warehousing concepts
- You are comfortable exploring potentially ambiguous business problems and enjoy finding technical solutions to them
- You have experience building robust and reliable data sets requiring a high level of control
- You’re keen to learn more about new technologies and their application in retail banking
- You strive for improvement, proactively identifying issues and opportunities and getting them prioritised
It would be a bonus if:
- You have multiple years of analytics experience, preferably in a fast moving tech company or consultancy
- Experience working with governance reporting or financial crime
- We can help you relocate to London & we can sponsor visas.
- This role can be based in our London office or remotely within the UK
- 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.
- 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, we'll make this happen whenever we can - whether this is to help you meet other commitments or strike a great work-life balance.
- The application process consists of a 30 min phone call with a recruiter, an initial call with someone from the team, followed by a practical written exercise and 2-3 video interviews. We promise not to ask you any brain teasers or trick questions.
Equal Opportunity Statement
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.
We're an equal opportunity employer. All applicants will be considered for employment without attention to ethnicity, religion, sexual orientation, gender identity, family or parental status, national origin, veteran, neurodiversity status or disability status.