At a Glance
- Tasks: Use data analysis and machine learning to combat fraud and boost customer profits.
- Company: Join LexisNexis Risk Solutions, a leader in risk management.
- Benefits: Competitive salary, flexible working options, and opportunities for professional growth.
- Other info: Collaborative team environment with exciting challenges and career advancement.
- Why this job: Make a real-world impact by protecting businesses from fraud.
- Qualifications: Strong Python and SQL skills, with experience in fraud or risk analysis.
The predicted salary is between 50000 - 70000 £ per year.
LexisNexis Risk Solutions is looking for a data scientist to join their team in the United Kingdom. The ideal candidate will leverage data analysis and machine learning to reduce fraud losses and enhance customer profitability. In this role, you will collaborate with internal teams to implement models that protect revenue against fraud.
Key responsibilities include:
- Developing machine learning models
- Defining features to capture fraud behaviours
- Crafting presentations that deliver insights effectively
Applicants should have strong skills in Python and SQL, with experience in the fraud or risk domains.
Fraud Risk Data Scientist - Real-World Impact & ML in London employer: LexisNexis Risk Solutions
At LexisNexis Risk Solutions, we pride ourselves on fostering a collaborative and innovative work culture that empowers our employees to make a real-world impact. As a Fraud Risk Data Scientist in the UK, you will not only have the opportunity to develop cutting-edge machine learning models but also benefit from continuous professional growth and a supportive environment that values your contributions. Join us to be part of a team that is dedicated to enhancing customer profitability while tackling fraud head-on.
StudySmarter Expert Advice🤫
We think this is how you could land Fraud Risk Data Scientist - Real-World Impact & ML in London
✨Tip Number 1
Network like a pro! Reach out to current employees at LexisNexis Risk Solutions on LinkedIn. A friendly message can go a long way in getting your foot in the door.
✨Tip Number 2
Show off your skills! Prepare a mini-project or case study that showcases your data analysis and machine learning prowess. This will help you stand out during interviews.
✨Tip Number 3
Practice makes perfect! Get comfortable with common interview questions related to fraud risk and machine learning. We recommend doing mock interviews with friends or using online platforms.
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets noticed. Plus, it shows you’re genuinely interested in joining the team at LexisNexis Risk Solutions.
We think you need these skills to ace Fraud Risk Data Scientist - Real-World Impact & ML in London
Some tips for your application 🫡
Show Off Your Skills:Make sure to highlight your Python and SQL skills in your application. We want to see how you can leverage these tools to tackle fraud and enhance profitability, so don’t hold back!
Tailor Your Experience:When writing your application, focus on your experience in the fraud or risk domains. We’re looking for candidates who can demonstrate their understanding of these areas, so make it relevant to the role.
Craft Clear Presentations:Since you'll be crafting presentations to deliver insights, include examples of how you've effectively communicated complex data findings in the past. We love clarity and creativity!
Apply Through Our Website:Don’t forget to apply through our website! It’s the best way for us to receive your application and ensures you’re considered for this exciting opportunity with LexisNexis Risk Solutions.
How to prepare for a job interview at LexisNexis Risk Solutions
✨Know Your Data Inside Out
Make sure you’re well-versed in data analysis and machine learning concepts, especially as they relate to fraud detection. Brush up on your Python and SQL skills, and be ready to discuss specific projects where you've successfully implemented models or analysed data to combat fraud.
✨Showcase Your Collaboration Skills
Since this role involves working with internal teams, prepare examples of how you've effectively collaborated in the past. Think about times when you’ve worked cross-functionally to implement a solution or present findings, and be ready to share those stories.
✨Prepare for Technical Questions
Expect technical questions that test your understanding of machine learning algorithms and their application in fraud risk. Review common algorithms and be prepared to explain how you would approach defining features to capture fraud behaviours in a real-world scenario.
✨Craft Engaging Presentations
You’ll need to communicate insights effectively, so practice presenting complex data in a clear and engaging way. Consider creating a mock presentation based on a past project, focusing on how you conveyed your findings and the impact they had on decision-making.
