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- Tasks: Develop machine learning solutions to detect fraud in real-time.
- Company: Global bank payment company focused on innovation and security.
- Benefits: Competitive pay, hybrid work model, and comprehensive benefits.
- Why this job: Join a mission to combat fraud and make a difference in fintech.
- Qualifications: Strong STEM background and experience in predictive modelling.
- Other info: Collaborative environment with opportunities for growth and innovation.
The predicted salary is between 36000 - 60000 £ per year.
A global bank payment company is seeking a Fraud Prevention Data Scientist to develop ML solutions for fraud detection. You will work closely with engineers and analysts, ensuring models are deployed effectively within the organization's operations.
Ideal candidates will have:
- A strong STEM background
- Experience with predictive modeling
- A passion for driving innovation in fraud prevention
The position offers a hybrid work model and includes competitive compensation and benefits.
Fraud Prevention Data Scientist — Real-Time ML for Fintech in London employer: GoCardless
Contact Detail:
GoCardless Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Fraud Prevention Data Scientist — Real-Time ML for Fintech in London
✨Tip Number 1
Network like a pro! Reach out to folks in the fintech space, especially those working in fraud prevention. A friendly chat can open doors and give you insights that might just land you that dream job.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your predictive modelling projects. Whether it's a GitHub repo or a personal website, having tangible examples of your work can really impress potential employers.
✨Tip Number 3
Prepare for the interview like it’s the final exam! Research the company’s current fraud prevention strategies and think about how your ML solutions can enhance them. Tailoring your answers to their needs will make you stand out.
✨Tip Number 4
Don’t forget to apply through our website! We’ve got loads of opportunities waiting for you, and applying directly can sometimes give you an edge. Plus, we love seeing candidates who are proactive!
We think you need these skills to ace Fraud Prevention Data Scientist — Real-Time ML for Fintech in London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your STEM background and any relevant experience in predictive modelling. We want to see how your skills align with the role of a Fraud Prevention Data Scientist, so don’t hold back on showcasing your achievements!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to express your passion for fraud prevention and innovation. We love seeing candidates who can articulate why they’re excited about this role and how they can contribute to our mission.
Showcase Your Technical Skills: Don’t forget to mention your technical skills related to machine learning and data analysis. We’re looking for someone who can develop effective ML solutions, so be specific about the tools and technologies you’ve used in the past.
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the position. Plus, it shows you’re keen on joining our team!
How to prepare for a job interview at GoCardless
✨Know Your ML Stuff
Make sure you brush up on your machine learning concepts, especially those related to fraud detection. Be ready to discuss your experience with predictive modelling and how you've applied it in real-world scenarios. This will show that you’re not just familiar with the theory but can also implement it effectively.
✨Showcase Your STEM Background
Highlight your educational background and any relevant projects that demonstrate your analytical skills. Be prepared to explain how your STEM knowledge has helped you solve complex problems, particularly in the context of fraud prevention. This will help the interviewers see your potential fit for the role.
✨Collaboration is Key
Since you'll be working closely with engineers and analysts, emphasise your teamwork skills. Share examples of past collaborations where you successfully deployed models or worked on cross-functional projects. This will illustrate your ability to integrate into their operations smoothly.
✨Passion for Innovation
Express your enthusiasm for driving innovation in fraud prevention. Discuss any new techniques or technologies you’ve explored and how they could be applied in a fintech environment. Showing that you’re proactive about staying ahead of trends will make you stand out as a candidate.
