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- Tasks: Partner with experts to analyze data and combat financial crime.
- Company: Join Monzo, a leader in making money work for everyone.
- Benefits: Enjoy flexible hours, a £1,000 learning budget, and remote work options.
- Why this job: Make a real impact by improving data accuracy and fighting financial crime.
- Qualifications: Solid SQL skills and a passion for data-driven decision-making required.
- Other info: Diversity and inclusion are core values; we welcome all applicants.
The predicted salary is between 36000 - 60000 £ per year.
You will be responsible for partnering with subject matter experts in financial crime to surface key insights that will help drive decision-making, and using data to solve financial crime problems. You will work together with other members of the data discipline to maintain high quality, accurate data that our colleagues can rely on, improving our ability to fight financial crime and keep customers safe. Some of the problems you might work on include monitoring our financial crime detection and prevention systems, helping our investigators do their job efficiently and effectively, and helping Monzo maintain transparency and effective reporting with its regulators.
Your day-to-day
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Build robust data models, reports, dashboards and visualisations (mostly in BigQuery SQL and Looker) that support the financial crime team in its mission.
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Translate regulatory reporting requirements into highly accurate data models and set the strategy for how we ensure the best possible data accuracy
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Investigate and effectively work with colleagues from other disciplines to address and improve data quality
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Conduct deep dives into various financial crime systems for financial crime detection, prevention, investigation and victim handling to identify key business opportunities
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Develop and drive data solutions that improve our ability to fight financial crime and keep customers safe
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Note: this role is more focused on developing dashboards, business reporting, high quality tables and data pipelines; it is not focused on advanced analytics or machine learning. If you are more interested in that type of work, consider applying to one of our data scientist roles., This role can be based in our London office, but we’re open to distributed working within the UK (with ad hoc meetings in London)
We offer flexible working hours and trust you to work enough hours to do your job well, and at times that suit you and your team.
£1,000 learning budget each year to use on books, training courses and conferences.
We will set you up to work from home; all employees are given Macbooks and for fully remote workers we will provide extra support for your work-from-home setup.
Plus lots more! .
The Interview Process:
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Recruiter Call
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Initial Call
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Take home task
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Final interview including a technical case and a behavioural interview
Our average process takes around 2-3 weeks but we will always work around your availability.
You will have the chance to speak to our recruitment team at various points during your process but if you do have any specific questions or want to talk through reasonable adjustments ahead of or during application please us at any point on tech-hiring@monzo.com
We have some guidelines on using Artificial Intelligence (AI) to ace an application and interview at Monzo.
Equal opportunities for everyone
Diversity and inclusion are a priority for us and we’re making sure we have lots of support for all of our people to grow at Monzo. At Monzo, we’re embracing diversity by 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. You can read more in our , and 2023
We’re an equal opportunity employer. All applicants will be considered for employment without attention to age, ethnicity, religion, sex, sexual orientation, gender identity, family or parental status, national origin, or veteran, neurodiversity or disability status.
LI-SL1 #LI-Remote
Equal opportunities for everyone
Diversity and inclusion are a priority for us and we’re making sure we have lots of support for all of our people to grow at Monzo. At Monzo, we’re embracing diversity by 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. You can read more in our , 2023 and 2023
We’re an equal opportunity employer. All applicants will be considered for employment without attention to age, ethnicity, religion, sex, sexual orientation, gender identity, family or parental status, national origin, or veteran, neurodiversity or disability status.
If you have a preferred name, please use it to apply. We don’t need full or birth names at application stage
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You’re keen to support the business by developing dashboards, high quality tables and data pipelines.
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You’re impact driven and eager to have a real positive impact on the company, product, users and very importantly your colleagues as well
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You’re passionate about data and using that data to improve & inform business decisions
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You’re motivated by solving challenging problems, and communicating and collaborating closely with subject matter experts on those solutions
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You’re as comfortable getting hands-on as taking a step back and thinking strategically
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You have a self-starter mindset; you proactively identify issues and opportunities and tackle them without being told to do so
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You’re a team player whom your colleagues can rely on
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You have solid grounding in SQL
Data Analyst, FinCrime employer: Monzo
Contact Detail:
Monzo Recruiting Team
tech-hiring@monzo.com
StudySmarter Expert Advice 🤫
We think this is how you could land Data Analyst, FinCrime
✨Tip Number 1
Familiarize yourself with BigQuery SQL and Looker, as these are essential tools for the role. Consider building a small project or dashboard using these technologies to showcase your skills during the interview process.
✨Tip Number 2
Understand the financial crime landscape and the specific challenges that organizations face in this area. Being able to discuss current trends and issues will demonstrate your genuine interest and knowledge during interviews.
✨Tip Number 3
Prepare to discuss your experience with data quality improvement and how you've tackled similar challenges in the past. Highlight any specific examples where your actions led to measurable improvements.
✨Tip Number 4
Showcase your collaborative skills by preparing examples of how you've worked with cross-functional teams. This role emphasizes teamwork, so being able to illustrate your ability to communicate and collaborate effectively is key.
We think you need these skills to ace Data Analyst, FinCrime
Some tips for your application 🫡
Understand the Role: Make sure to thoroughly read the job description for the Data Analyst position. Highlight the key responsibilities and required skills, such as building dashboards and data models in BigQuery SQL and Looker.
Tailor Your CV: Customize your CV to reflect your experience with data analysis, dashboard creation, and SQL. Use specific examples that demonstrate your ability to solve financial crime problems and improve data quality.
Craft a Compelling Cover Letter: Write a cover letter that showcases your passion for data and your impact-driven mindset. Mention how your skills align with the company's mission to fight financial crime and keep customers safe.
Prepare for the Interview Process: Familiarize yourself with the interview process outlined in the job description. Be ready to discuss your technical skills and provide examples of past projects during the initial call and final interview.
How to prepare for a job interview at Monzo
✨Show Your Passion for Data
Make sure to express your enthusiasm for data and how it can drive business decisions. Share examples of how you've used data in the past to solve problems or improve processes.
✨Prepare for Technical Questions
Since this role involves building dashboards and data models, be ready to discuss your experience with SQL and tools like BigQuery and Looker. Practice explaining your thought process when creating data solutions.
✨Demonstrate Collaboration Skills
Highlight your ability to work with subject matter experts and other teams. Prepare examples of how you've successfully collaborated on projects to improve data quality or solve financial crime issues.
✨Understand Regulatory Requirements
Familiarize yourself with the regulatory landscape related to financial crime. Be prepared to discuss how you would translate these requirements into accurate data models and reporting.
