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- Tasks: Investigate suspicious behaviour and analyse data to mitigate fraud risks.
- Company: Join LexisNexis Risk Solutions, a leader in risk assessment and fraud detection.
- Benefits: Enjoy flexible working options and opportunities for professional growth.
- Why this job: Make a real-world impact by protecting businesses from fraud while collaborating with global teams.
- Qualifications: Strong skills in Python and SQL; experience with BI tools is a plus.
- Other info: Work with cutting-edge technology on a real-time fraud detection platform.
The predicted salary is between 36000 - 60000 £ per year.
Conducting in-depth reviews of complex fraud cases: Identifying trends and actionable insights, documenting findings, and making clear recommendations on how to mitigate risk.
Using SQL and Python skills: Increasing fraud capture, reducing false positives, analyzing customer data offline to expose patterns, tuning policies statistically, producing executive reports, and owning the end-to-end delivery of recommendations by writing rules into the ThreatMetrix decision engine.
Building dashboards & reports: Tracking the value delivered, focusing on external-facing dashboards that surface key insights to each customer.
Data storytelling and presentation: Crafting stories through data, delivering industry-leading presentations to external and executive audiences with non-technical backgrounds.
Project management: Scoping, planning, and delivering customer-focused projects including root cause analysis, reports, dashboards, rule mining, and health checks. Demonstrating professionalism and customer-centricity in interactions via phone, email, and chat.
Collaboration: Working with ThreatMetrix teams including Products, Engineering, Sales, and Professional Services worldwide to redefine best practices.
Experience required: Within a Fraud Strategy or Fraud Analytics function, proficient in SQL, Python, and BI tools like SuperSet, PowerBI, Tableau (bonus), with experience in fraud system management (ThreatMetrix, Emailage, Featurespace, Hunter, Iovation, BioCatch, Actimize Falcon, etc.), and interest or experience in consulting within risk, fraud, or payments industries.
Skills and qualities: Attention to detail, ability to build external and executive reports, multi-tasking, prioritization, and ability to excel in a fast-paced environment with changing priorities.
About the Business: LexisNexis Risk Solutions helps businesses assess risk, drive revenue, optimize operations, and improve customer experience across areas like AML, identity verification, fraud mitigation, and customer data management.
About our Team: A team of analysts using global data from a large real-time fraud detection platform to optimize solutions for enterprise customers.
About the Role: Using data analysis to investigate suspicious behavior, providing insights that reduce fraud losses, lower customer friction, and increase profitability. Analyzing billions of transactions per month for clients in financial services, insurance, e-commerce, and on-demand services, collaborating across teams to build effective policies against motivated attackers.
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Fraud Data Analyst employer: LexisNexis Risk Solutions
Contact Detail:
LexisNexis Risk Solutions Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Fraud Data Analyst
✨Tip Number 1
Familiarise yourself with the latest trends in fraud detection and risk management. Understanding the current landscape will not only help you during interviews but also demonstrate your genuine interest in the field.
✨Tip Number 2
Network with professionals in the fraud analytics space. Attend industry events or webinars to connect with people who work at LexisNexis or similar companies, as they can provide valuable insights and potentially refer you for the position.
✨Tip Number 3
Brush up on your SQL and Python skills by working on real-world projects or contributing to open-source initiatives. This practical experience will give you a competitive edge and show your commitment to continuous learning.
✨Tip Number 4
Prepare to discuss specific examples of how you've used data analysis to solve problems in previous roles. Being able to articulate your thought process and the impact of your work will resonate well with the interviewers.
We think you need these skills to ace Fraud Data Analyst
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with data analysis, SQL, and Python. Include specific examples of how you've used these skills in previous roles, especially in fraud detection or risk management.
Craft a Compelling Cover Letter: In your cover letter, express your enthusiasm for the role and the company. Discuss your analytical skills and how they align with the responsibilities outlined in the job description, particularly your ability to identify trends and provide actionable insights.
Showcase Relevant Projects: If you have worked on projects involving BI tools or fraud detection, be sure to mention them. Describe your role, the tools you used, and the impact your work had on the project outcomes.
Prepare for Technical Questions: Be ready to discuss your technical skills in detail, particularly your proficiency in SQL and Python. You may be asked to solve problems or analyse data during the interview process, so brush up on relevant concepts and practice coding challenges.
How to prepare for a job interview at LexisNexis Risk Solutions
✨Showcase Your Technical Skills
Make sure to highlight your proficiency in Python and SQL during the interview. Be prepared to discuss specific projects where you've used these skills, especially in relation to fraud detection or data analysis.
✨Demonstrate Analytical Thinking
Prepare to discuss how you approach problem-solving, particularly in complex fraud cases. Use examples that illustrate your ability to identify trends and derive actionable insights from data.
✨Prepare for Scenario-Based Questions
Expect questions that present hypothetical fraud scenarios. Practice articulating your thought process on how you would investigate these cases and what steps you would take to mitigate risks.
✨Communicate Clearly and Effectively
Since you'll be presenting findings to non-technical audiences, practice explaining complex data insights in simple terms. This will demonstrate your ability to craft a compelling narrative through data.
