Data Analyst, Operations & Financial Crime
We're looking for a Data Analyst excited to help build the bank of the future!
At Monzo, 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. You'll have the opportunity to help us ensure the quality of the work done in Financial Crime in 2021 and help us continue to build a bank safely, and in control.
This role will be supporting the Assurance team, and will focus on making sure we can measure and understand the performance of staff members working on key operational projects within Financial Crime. You’ll be responsible for working with our FinCrime Assurance Lead to ensure we check the right number and type of tasks to have confidence in our metrics, that our scoring is robust and fair, and that any root causes of poor performance are identified. You’ll also be responsible for providing key stakeholders across the business with self-service dashboards for real time understanding of the metrics you have created.
We work in cross-functional squads where every data analyst is a member of a central Data Discipline but will be fully embedded into one area (for this role, it will be embedded within the Quality Assurance team, who monitor the quality of the work our Customer Operations team does, with a specific focus on Financial Crime Quality Assurance).
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
As part of your role, you'll:
- Build robust data models, reports and visualisations (mostly in BigQuery SQL) that support the Quality Assurance team in ensuring they’re checking the right tasks at the right time, and that the information they collect is easy to understand and use
- Collect, analyse, and disseminate information and analysis on the results of our quality assurance processes.
- Develop, maintain, and modify strategies for quality assurance and accreditation of our Customer Operations staff. You’ll start with a focus on work done in Financial Crime, but with a view to building sustainable solutions that can be used across Operations at Monzo.
- Identify information and data gaps, create techniques and collation processes to close such gaps
- Support the business with analytical deep dives to identify root causes of issues uncovered by quality assurance checks
- Provide key stakeholders across the business with self-service dashboards for real time understanding of the metrics you have created, using Looker
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:
- 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 passionate about data and using that data to improve & inform business decisions
- 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
Nice to haves:
- You have experience in data analytics, preferably in a fast moving tech company
- You have experience of using a BI tool like Looker to provide dashboards and self-serve analysis tools to stakeholders
Our interview process is normally a phone interview, a take home task and call to discuss it, and 2-3 hours of onsite interviews. We promise not to ask you any brain teasers or trick questions.
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.
Questions about this role? Head over to our careers page to read our FAQs (www.monzo.com/careers)
Explore more AI/ML/Data Science career opportunities
- Open Head of Data Science Jobs
- Open Data Scientist II Jobs
- Open Sr. Machine Learning Engineer Jobs
- Open Data Engineer III Jobs
- Open Applied Data Scientist - B2B Sales Incrementality Jobs
- Open Data Operations Analyst Jobs
- Open Senior Marketing Data Analyst Jobs
- Open Data Science Manager Jobs
- Open Data Engineer - Toronto Hub Jobs
- Open Senior Machine Learning Scientist Jobs
- Open Senior Data Engineer - Toronto Hub Jobs
- Open Data Science Intern Jobs
- Open Business Data Analyst Jobs
- Open Lead Data Analyst Jobs
- Open Manager, Data Engineering Jobs
- Open Software Engineer, Machine Learning Jobs
- Open Data Engineering Manager (Data Science & Analytics) Jobs
- Open Machine Learning Scientist Jobs
- Open Software Engineer - Machine Learning Jobs
- Open Data Engineer: Business Intelligence Jobs
- Open Data Analytics Manager Jobs
- Open BI Data Analyst Jobs
- Open Senior Data Engineer - Streaming Jobs
- Open Staff Data Scientist Jobs
- Open Data Science Consultant Jobs
- Open Economics-related jobs
- Open Kafka-related jobs
- Open Looker-related jobs
- Open PyTorch-related jobs
- Open Kubernetes-related jobs
- Open Consulting-related jobs
- Open Healthcare-related jobs
- Open Data pipelines-related jobs
- Open Pandas-related jobs
- Open Data Warehousing-related jobs
- Open Data Mining-related jobs
- Open NLP-related jobs
- Open Distributed Systems-related jobs
- Open Open Source-related jobs
- Open BigQuery-related jobs
- Open Computer Vision-related jobs
- Open Linux-related jobs
- Open Scikit-Learn-related jobs
- Open NoSQL-related jobs
- Open MySQL-related jobs
- Open NumPy-related jobs
- Open Keras-related jobs
- Open MongoDB-related jobs
- Open Cassandra-related jobs