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- Tasks: Drive fraud strategy and protect the business from financial crime using data analysis.
- Company: Join N Brown, a leading UK digital retail platform with a focus on inclusivity.
- Benefits: Enjoy hybrid working, 24 days holiday, annual bonuses, and mental health support.
- Why this job: Make a real impact in fraud prevention while collaborating with diverse teams.
- Qualifications: Degree in STEM and experience in fraud data analysis required.
- Other info: Be part of a culture that values diversity and promotes career growth.
The predicted salary is between 45000 - 55000 £ per year.
The role involves joining the Financial Services team as a Senior Fraud Data Analyst, responsible for driving fraud strategy to protect the business from fraud and financial crime. The ideal candidate will be an experienced fraud strategy professional, highly data literate, with knowledge of platforms and techniques to combat fraud, and an understanding of the balance between minimising fraud and maximising sales.
Key responsibilities include:
- Providing support in all aspects of consumer fraud and financial crime, including knowledge of 1st and 3rd party fraud typologies and fraud detection data, techniques, and platforms.
- Overseeing the fraud control rule structure and working closely with third-party fraud prevention solution providers.
- Designing and implementing fraud strategies to detect and prevent consumer credit fraud.
- Using data analysis and modelling techniques to optimise rules for detecting fraud while minimising impact on sales.
- Monitoring KPIs and KRIs to ensure new fraud risks are detected and strategy changes are effective.
- Building collaborations with other business areas to ensure initiatives align with fraud risk appetite.
- Maintaining knowledge of regulatory changes to ensure compliance with governance and financial crime standards.
Required skills and experience:
- A degree in a STEM subject.
- Previous experience in data analysis and strategy development for fraud prevention.
- Proficiency in SQL, SAS, or Python for data mining and analysis.
- Excellent presentation skills and ability to explain complex analysis simply.
- Strong organisational skills and attention to detail.
- Ability to collaborate effectively across the business.
- Self-starter who can work with ambiguity.
Desirable qualifications include experience in a consumer fraud analytical role for an online retail lender and familiarity with fraud decision systems.
Benefits include hybrid working, 24 days holiday, annual bonus scheme, enhanced maternity leave, company pension, mental health support, colleague discounts, life assurance, and paid volunteer time.
N Brown is a leading UK digital retail platform, committed to inclusivity and creating a diverse workforce. We offer a happy and inclusive culture and are proud to have been named one of The Sunday Times Best Places to Work 2024.
Senior Fraud Data Analyst in Manchester employer: JD Williams
Contact Detail:
JD Williams Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Fraud Data Analyst in Manchester
✨Tip Number 1
Network like a pro! Reach out to your connections in the industry, especially those who work at N Brown or similar companies. A friendly chat can open doors and give you insider info on the role.
✨Tip Number 2
Prepare for the interview by brushing up on your fraud detection knowledge. Be ready to discuss specific strategies you've used in the past and how they could apply to N Brown's needs.
✨Tip Number 3
Show off your analytical skills during the interview! Bring examples of your data analysis work, especially any that relate to fraud prevention. Visuals can really help make your case.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you’re genuinely interested in joining the team.
We think you need these skills to ace Senior Fraud Data Analyst in Manchester
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the Senior Fraud Data Analyst role. Highlight your experience in fraud strategy and data analysis, and don’t forget to mention any relevant tools like SQL or Python that you’ve used.
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're passionate about fraud prevention and how your skills align with our mission at N Brown. Keep it concise but impactful!
Showcase Your Analytical Skills: In your application, be sure to showcase your analytical skills. Provide examples of how you've used data to drive decisions in previous roles, especially in fraud detection and prevention.
Apply Through Our Website: We encourage you to apply through our website for the best chance of getting noticed. It’s super easy, and you’ll be able to track your application status directly!
How to prepare for a job interview at JD Williams
✨Know Your Fraud Strategies
Before the interview, brush up on various fraud strategies and detection techniques. Be ready to discuss specific examples of how you've used data analysis to combat fraud in your previous roles. This will show that you’re not just familiar with the concepts but have practical experience applying them.
✨Master the Data Tools
Make sure you're comfortable with SQL, SAS, or Python, as these are crucial for the role. Prepare to demonstrate your ability to extract and analyse large datasets. You might even want to bring a sample project or two to discuss how you’ve used these tools effectively in the past.
✨Showcase Your Presentation Skills
Since you'll need to present complex analyses simply, practice explaining your past projects to someone unfamiliar with the subject. This will help you articulate your findings clearly during the interview, showcasing your communication skills and making a strong impression.
✨Build Relationships
Highlight your experience in collaborating with different teams, such as Risk and Compliance or Digital Technology. Be prepared to share examples of how you’ve built effective working relationships in the past, as this is key for the role and will demonstrate your ability to work cross-functionally.