At a Glance
- Tasks: Develop and implement risk models to detect and manage fraud effectively.
- Company: Join Checkout.com, a leading fintech company with a focus on innovation.
- Benefits: Competitive salary, flexible working hours, and opportunities for professional growth.
- Other info: Dynamic team environment with excellent career advancement opportunities.
- Why this job: Make a real impact in the fintech world by tackling fraud and risk challenges.
- Qualifications: Experience with large data sets, SQL, and programming languages like Python or R.
The predicted salary is between 60000 - 80000 £ per year.
As a Senior Risk Data Scientist at Checkout.com, you will play a critical role in the Risk Team, developing rules and models to effectively detect, prevent and manage risk within the overall Checkout.com portfolio.
About You
- Worked with large data sets in a data-driven environment.
- Used SQL skills to extract and model data from a variety of data sources.
- Programming language knowledge or experience (e.g., Python, R, Javascript) is essential.
- Strong understanding of credit risk principles and has worked in either payments or lending environments previously.
- Experience developing, maintaining and implementing PD, LGD, EAD models for ECL measurement purposes is preferred.
What you will be doing:
- Build and maintain data-driven risk identification processes.
- Devise advanced analytical methods to identify anomalies and patterns within large data sets.
- Developing and implementing Rating Scorecards, PD, LGD, EAD models.
- Maintain and optimise the current Credit Risk reporting system.
Manager, Fraud and Risk Strategist Enterprise Risk Management London employer: Checkout Ltd
At Checkout.com, we pride ourselves on being an exceptional employer, offering a dynamic work culture that fosters innovation and collaboration. Our London office provides employees with access to cutting-edge technology and resources, alongside ample opportunities for professional growth and development in the fast-paced world of risk management. Join us to be part of a team that values your contributions and supports your career aspirations in a meaningful way.
StudySmarter Expert Advice🤫
We think this is how you could land Manager, Fraud and Risk Strategist Enterprise Risk Management London
✨Tip Number 1
Network like a pro! Reach out to folks in the industry on LinkedIn or at events. A friendly chat can open doors that a CV just can't.
✨Tip Number 2
Show off your skills! If you’ve got experience with SQL, Python, or any other relevant tools, be ready to demonstrate your knowledge in interviews. Bring examples of your work to the table.
✨Tip Number 3
Research the company inside out. Understand their risk management strategies and be prepared to discuss how your experience aligns with their needs. It shows you’re genuinely interested!
✨Tip Number 4
Don’t forget to apply through our website! We love seeing candidates who take the initiative. Plus, it’s a great way to ensure your application gets noticed.
We think you need these skills to ace Manager, Fraud and Risk Strategist Enterprise Risk Management London
Some tips for your application 🫡
Show Off Your Data Skills:Make sure to highlight your experience with large data sets and SQL in your application. We want to see how you've used these skills in real-world scenarios, so don’t hold back!
Talk About Your Programming Experience:If you’ve got experience with programming languages like Python or R, let us know! Share specific examples of how you’ve used these tools to tackle risk-related challenges.
Demonstrate Your Understanding of Credit Risk:We’re looking for someone who really gets credit risk principles. In your application, mention any relevant experience in payments or lending environments to show us you’re the right fit.
Apply Through Our Website:Don’t forget to submit your application through our website! It’s the best way for us to keep track of your application and ensure it gets the attention it deserves.
How to prepare for a job interview at Checkout Ltd
✨Know Your Data Inside Out
Make sure you’re familiar with large data sets and how to manipulate them. Brush up on your SQL skills and be ready to discuss specific examples of how you've used data to identify risks or anomalies in previous roles.
✨Show Off Your Programming Skills
Since programming knowledge is essential, be prepared to talk about your experience with languages like Python, R, or Javascript. Consider bringing a portfolio of projects or code snippets that demonstrate your ability to develop models or analytical methods.
✨Understand Credit Risk Principles
Dive deep into credit risk principles and be ready to discuss how they apply to payments or lending environments. Think of real-world scenarios where you’ve implemented PD, LGD, or EAD models and be prepared to explain your thought process.
✨Prepare for Technical Questions
Expect technical questions related to risk identification processes and model development. Practice explaining complex concepts in simple terms, as this will show your ability to communicate effectively with both technical and non-technical stakeholders.
