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- Tasks: Enhance fraud detection rules and collaborate with data teams to combat financial crime.
- Company: Dynamic technology firm in the UK focused on innovation.
- Benefits: Competitive salary, flexible working hours, and opportunities for professional growth.
- Why this job: Join a mission-driven team tackling real-world financial challenges with data.
- Qualifications: Strong SQL skills and experience with complex datasets; ACI expertise is a plus.
- Other info: Fast-paced environment with potential for career advancement.
The predicted salary is between 36000 - 60000 £ per year.
A technology firm in the UK is hiring a Fraud & AML Detection Systems Specialist / BA to enhance detection rules and collaborate with data teams. Responsibilities include monitoring systems, producing reports, and interpreting financial crime trends.
The ideal candidate must have strong SQL skills and experience in managing complex datasets, with expertise in ACI Proactive Risk Management preferred.
Fraud & AML Detection Systems Specialist — Data-Driven BA in Leeds employer: GIOS Technology
Contact Detail:
GIOS Technology Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Fraud & AML Detection Systems Specialist — Data-Driven BA in Leeds
✨Tip Number 1
Network like a pro! Reach out to folks in the industry on LinkedIn or at local meetups. You never know who might have the inside scoop on job openings or can put in a good word for you.
✨Tip Number 2
Show off your skills! If you've got strong SQL skills, consider creating a mini-project or a portfolio piece that showcases your ability to manage complex datasets. This can really set you apart during interviews.
✨Tip Number 3
Prepare for those tricky questions! Brush up on your knowledge of financial crime trends and ACI Proactive Risk Management. Being able to discuss these topics confidently can make a huge difference in your interview.
✨Tip Number 4
Don't forget to apply through our website! We’ve got loads of resources to help you ace your application and land that dream job as a Fraud & AML Detection Systems Specialist.
We think you need these skills to ace Fraud & AML Detection Systems Specialist — Data-Driven BA in Leeds
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your SQL skills and experience with complex datasets. We want to see how your background aligns with the role of a Fraud & AML Detection Systems Specialist, so don’t hold back on showcasing relevant projects!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you’re passionate about fraud detection and how your skills can help us enhance our detection rules. Keep it concise but impactful!
Showcase Your Analytical Skills: In your application, give examples of how you've monitored systems or produced reports in the past. We love data-driven insights, so share any experiences that demonstrate your ability to interpret financial crime trends.
Apply Through Our Website: We encourage you to apply directly through our website for a smoother process. It helps us keep track of applications better and ensures you don’t miss out on any important updates from us!
How to prepare for a job interview at GIOS Technology
✨Know Your SQL Inside Out
Since strong SQL skills are a must for this role, make sure you brush up on your SQL knowledge. Be prepared to discuss your experience with complex datasets and even tackle some SQL queries during the interview.
✨Understand Financial Crime Trends
Familiarise yourself with current trends in financial crime and AML regulations. Being able to discuss recent developments or case studies will show that you're not just knowledgeable but also genuinely interested in the field.
✨Showcase Your Reporting Skills
Prepare examples of reports you've produced in previous roles. Highlight how your insights have influenced decision-making or improved detection systems. This will demonstrate your ability to translate data into actionable strategies.
✨Collaborate Like a Pro
This role involves working closely with data teams, so be ready to talk about your collaboration experiences. Share specific instances where teamwork led to successful outcomes, especially in enhancing detection rules or managing projects.
