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- Tasks: Lead analytics to enhance financial crime detection and optimise monitoring systems.
- Company: Global banking organisation with a focus on innovation and compliance.
- Benefits: Hybrid work model, competitive salary, and opportunities for professional growth.
- Other info: Collaborative environment with a focus on continuous improvement and learning.
- Why this job: Make a real impact in fighting financial crime using advanced analytics.
- Qualifications: Experience in financial crime analytics and strong analytical skills required.
The predicted salary is between 60000 - 80000 £ per year.
London/Hybrid, 3 days in the office. My client is a Global Banking organisation seeking a highly skilled Data Scientist to join their EMEA Financial Crime Operations team. You will work within the Intelligence & Analytics function, responsible for enhancing the effectiveness of transaction monitoring and sanctions screening systems. This is a hands-on, data-driven role with a focus on leveraging advanced analytics, optimisation techniques, and model validation to strengthen financial crime detection across multiple jurisdictions. This role will suit an expert in Financial Crime Analytics or a Data Scientist with a background in transaction monitoring and sanctions.
Key Responsibilities:- Lead a specialist analytics team to develop, optimise, and enhance segmentation, tuning, and monitoring logic in transaction monitoring and sanctions screening programs.
- Coordinate and implement detection scenarios to identify potential financial crime activity.
- Support the design, tuning, and optimisation of automated monitoring and sanctions screening models, ensuring high alert quality and efficiency.
- Contribute to the development and validation of models, including scenario calibration, segmentation logic, and optimisation frameworks.
- Collaborate with regional analytics teams to share learnings and implement global improvements in financial crime detection.
- Assist in updating policies, procedures, and governance frameworks related to transaction monitoring and sanctions screening activities.
- Translate complex analytical insights into actionable recommendations for operational teams, senior management, and regulators.
- Oversee model validation, memorialise assumptions, and ensure regulatory alignment with AML, sanctions, and financial crime compliance standards.
- Proven track record in transaction monitoring and financial crime detection, with experience in sanctions screening highly desirable.
- Strong experience in global banking organisations, consultancy, or regulatory environment, with strong analytical and problem-solving skills.
- Hands-on experience with data engineering and data science techniques: building scalable analytics pipelines, model development, and optimisation frameworks.
- Transaction monitoring system experience would be advantageous such as Actmize, Fiserve AML, SAS AML, FICO TONBELLER, Oracle Mantas.
- Advanced analytical tools and programming languages, experience of Python is essential, advantageous to have exposure to SQL, Spark, Databricks, Snowflake, Pandas, or similar.
- Strong knowledge of financial crime regulations, including AML, sanctions, and monitoring requirements across EMEA jurisdictions.
- Excellent written and verbal communication skills, with the ability to present complex analytical insights clearly to senior management and regulatory bodies.
- Degree or equivalent industry-standard qualification in a quantitative, technical, or finance-related discipline.
Data Scientist - Financial Crime employer: Magnit Global
Contact Detail:
Magnit Global Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Scientist - Financial Crime
✨Tip Number 1
Network like a pro! Reach out to folks in the financial crime and data science sectors on LinkedIn. Join relevant groups, attend webinars, and don’t be shy about asking for informational interviews. You never know who might have the inside scoop on job openings!
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects related to transaction monitoring and financial crime analytics. Use platforms like GitHub to share your code and analyses. This will give potential employers a taste of what you can bring to the table.
✨Tip Number 3
Prepare for those interviews! Research common questions for data scientists in the financial sector and practice your responses. Be ready to discuss your experience with tools like Python, SQL, and any specific transaction monitoring systems you've worked with.
✨Tip Number 4
Don’t forget to apply through our website! We’ve got loads of opportunities that might just be the perfect fit for you. Plus, applying directly can sometimes give you a leg up in the hiring process. So, get your application in and let’s get you that dream job!
We think you need these skills to ace Data Scientist - Financial Crime
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the Data Scientist role in Financial Crime. Highlight your experience with transaction monitoring and any relevant analytical tools you've used. We want to see how your skills match what we're looking for!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're passionate about financial crime analytics and how your background makes you a perfect fit for our team. Keep it engaging and relevant to the job description.
Showcase Your Technical Skills: Don’t forget to highlight your hands-on experience with data engineering and programming languages like Python. We love seeing candidates who can demonstrate their technical prowess, especially in building scalable analytics pipelines!
Apply Through Our Website: We encourage you to apply through our website for a smoother application process. It helps us keep track of your application and ensures you don’t miss out on any important updates from us!
How to prepare for a job interview at Magnit Global
✨Know Your Data Science Tools
Make sure you're well-versed in the analytical tools and programming languages mentioned in the job description, especially Python. Brush up on your SQL skills too, as they might ask you to demonstrate your knowledge during the interview.
✨Understand Financial Crime Regulations
Familiarise yourself with the key financial crime regulations, particularly AML and sanctions across EMEA jurisdictions. Being able to discuss these regulations confidently will show that you’re not just a data whiz but also understand the context of your work.
✨Prepare Real-World Examples
Think of specific instances where you've successfully implemented analytics solutions or optimised monitoring systems. Be ready to share these examples, as they’ll help illustrate your hands-on experience and problem-solving skills.
✨Communicate Clearly
Practice explaining complex analytical insights in simple terms. You might need to present your findings to senior management or regulatory bodies, so being able to communicate effectively is crucial. Consider doing mock interviews to refine this skill.