We're looking for a curious, adaptable Financial Crime Governance Analyst to join our Financial Crime Data Science team at Monzo!

You'll be working in the intersection between data, engineering and our financial crime functions, forming part of a high performing cross disciplinary squad consisting of both data and engineering. You will be responsible for building downstream data models from backend services, identifying and driving process efficiency and ensuring timeliness and completeness of our financial crime data. You will be working in particular on important data assets within our financial crime regulatory and reporting space.

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

The role 

Working in a multi-disciplinary data and engineering squad, you will:

  • work closely with financial crime 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
  • integrate new data sources into our data warehouse
  • design, build and launch new data pipelines in production

 

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

Logistics

  • 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.

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