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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.
Key Skills/Experience:
- 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 Actimize, 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 in London employer: Magnit Global
Contact Detail:
Magnit Global Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Scientist - Financial Crime in London
✨Tip Number 1
Network like a pro! Reach out to people in the financial crime and data science sectors on LinkedIn. Join relevant groups and participate in discussions to get your name out there. You never know who might have a lead on that perfect job!
✨Tip Number 2
Prepare for interviews by brushing up on your technical skills. Since this role involves advanced analytics and model validation, be ready to discuss your experience with tools like Python and SQL. Practise explaining complex concepts in simple terms – it’ll impress the interviewers!
✨Tip Number 3
Showcase your projects! If you’ve worked on any relevant data science projects, make sure to highlight them during interviews. Bring along examples of how you’ve enhanced transaction monitoring or developed models – real-world applications speak volumes.
✨Tip Number 4
Don’t forget to apply through our website! We’ve got loads of resources to help you land that dream job. Plus, applying directly shows your enthusiasm and commitment to joining our team. Let’s get you started on this exciting journey!
We think you need these skills to ace Data Scientist - Financial Crime in London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV speaks directly to the job description. Highlight your experience in financial crime analytics and any relevant tools you've used, like Python or SQL. We want to see how your skills match up with 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 detection and how your background makes you a perfect fit for our team. Keep it engaging and personal – we love to see your personality come through!
Showcase Your Analytical Skills: In your application, don’t just list your skills; demonstrate them! Share specific examples of how you've used data science techniques to solve problems in transaction monitoring or sanctions screening. We’re all about those hands-on experiences!
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it shows you’re keen on joining our team at StudySmarter!
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 and any other relevant technologies like Spark or Databricks, as you might be asked to demonstrate your knowledge during the interview.
✨Understand Financial Crime Regulations
Familiarise yourself with the key financial crime regulations, particularly AML and sanctions requirements across EMEA jurisdictions. Being able to discuss these topics 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 in transaction monitoring or sanctions screening. Be ready to explain your thought process, the challenges you faced, and how you overcame them. This will help you stand out as a practical problem-solver.
✨Communicate Clearly
Practice explaining complex analytical insights in simple terms. You may need to present your findings to senior management or regulatory bodies, so being able to communicate effectively is crucial. Consider doing mock interviews with friends or colleagues to refine your delivery.