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- Tasks: Join a team of fraud experts to analyze risk and combat fraud effectively.
- Company: Be part of a dynamic company dedicated to enhancing payment security.
- Benefits: Enjoy a collaborative environment with opportunities for learning and growth.
- Why this job: Make a real impact in fraud prevention while working on exciting projects.
- Qualifications: 5+ years in e-commerce or payments, strong analytical skills, and SQL experience required.
- Other info: Flexibility to work weekends and holidays is necessary.
The predicted salary is between 36000 - 60000 £ per year.
*** 1 year Fixed-Term Contract ***
As a Risk Analyst , you will join a team of talented and dedicated fraud experts who play a pivotal role in fighting fraud and helping our customers succeed. Your work will make a big impact in advancing payment risk decisioning to the next level. The right candidate is an experienced fraud fighter with a love for learning, problem solving, and not afraid of a challenge. They enjoy being part of a close knit team and working on multiple projects simultaneously without compromising quality.
Here’s more of what you will get to do:
- Perform proactive risk analysis to identify risk factors and trends of potentially fraudulent activity on large datasets.
- Identify fraud trends, document and communicate findings, and lead in the development and implementation of new fraud prevention strategies.
- Support Risk Operations with process and tool improvements.
- Assist our internal teams by leading fraud and tool insights conversations with potential and existing merchants.
- Turn analysis into actionable insights for fraud mitigation initiatives, ad-hoc reports and presentations.
- Assist in special projects and ad-hoc assignments, upon request.
- Develop and maintain strong relationships with internal teams and external business partners.
Required skills that will allow you to thrive in this role:
- 5+ years experience in e-commerce, payments or risk-related industry with either traditional and non-traditional payment methods.
- Strong understanding of ecommerce payments landscape.
- Strong analytical skills and an understanding of how to utilize data to target improvements and solve problems.
- Experience with database language (e.g., SQL) as well as BI and reporting tools (Looker, Tableau, Splunk, etc.).
- Strong critical thinking skills with advanced judgment capability.
- Ability to manage multiple assignments while working independently.
- Strong communication skills with internal and external stakeholders.
- Flexibility to work weekends and holidays.
Desirable Skills:
- Experience in large scale data analysis, tools, and processes (e.g. Python, R).
- Experience with translating fraud trends into rule logic and/or feature suggestions.
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Risk Analyst - Fixed Term Contract employer: Menlo Ventures
Contact Detail:
Menlo Ventures Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Risk Analyst - Fixed Term Contract
✨Tip Number 1
Familiarize yourself with the latest trends in e-commerce and payment fraud. Stay updated on industry news and developments, as this knowledge will help you engage in meaningful conversations during interviews.
✨Tip Number 2
Network with professionals in the risk analysis and fraud prevention fields. Attend relevant webinars or local meetups to connect with others who can provide insights or even referrals for the position.
✨Tip Number 3
Brush up on your SQL and data visualization skills. Being able to demonstrate your proficiency with tools like Looker or Tableau during discussions can set you apart from other candidates.
✨Tip Number 4
Prepare to discuss specific examples of how you've identified and mitigated fraud in past roles. Having concrete stories ready will showcase your experience and problem-solving abilities effectively.
We think you need these skills to ace Risk Analyst - Fixed Term Contract
Some tips for your application 🫡
Understand the Role: Make sure to thoroughly read the job description for the Risk Analyst position. Highlight the key responsibilities and required skills, and think about how your experience aligns with them.
Tailor Your CV: Customize your CV to emphasize your relevant experience in e-commerce, payments, or risk-related industries. Include specific examples of your analytical skills and any tools you've used, such as SQL or BI reporting tools.
Craft a Compelling Cover Letter: Write a cover letter that showcases your passion for fighting fraud and problem-solving. Mention your experience with data analysis and how you can contribute to the team’s goals. Be sure to connect your past experiences with the responsibilities listed in the job description.
Highlight Team Collaboration: Since the role emphasizes teamwork, include examples in your application that demonstrate your ability to work collaboratively with internal teams and external partners. This will show that you are a good fit for their close-knit team environment.
How to prepare for a job interview at Menlo Ventures
✨Showcase Your Analytical Skills
Be prepared to discuss specific examples of how you've used data analysis to identify fraud trends in your previous roles. Highlight your experience with tools like SQL, Looker, or Tableau, and be ready to explain how you turned data insights into actionable strategies.
✨Demonstrate Problem-Solving Abilities
Since the role requires a strong problem-solving mindset, think of challenging situations you've faced in the past and how you overcame them. Use the STAR method (Situation, Task, Action, Result) to structure your responses.
✨Emphasize Team Collaboration
This position involves working closely with internal teams and external partners. Share experiences where you successfully collaborated on projects, highlighting your communication skills and ability to build strong relationships.
✨Prepare for Technical Questions
Expect questions related to your technical skills, especially around data analysis and fraud prevention strategies. Brush up on relevant concepts and be ready to discuss any programming languages or tools you are familiar with, such as Python or R.
