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- Tasks: Develop innovative solutions for fraud detection and financial crime prevention using Python and PySpark.
- Company: Leading technology and business services provider in Greater London.
- Benefits: Remote or hybrid work options, competitive salary, and professional development opportunities.
- Why this job: Join a dynamic team to combat financial crime and make a real difference.
- Qualifications: 5+ years of experience in data science and a solid understanding of Financial Crime domains.
- Other info: Flexible working arrangements based on client needs.
The predicted salary is between 54000 - 84000 £ per year.
A leading technology and business services provider in Greater London seeks an experienced Senior Data Scientist. The role requires expertise in Python and PySpark to develop innovative solutions for fraud detection and financial crime prevention.
Candidates should possess 5+ years in relevant fields and a solid understanding of Financial Crime domains. This position allows for remote or hybrid work based on client needs.
Senior Data Scientist – Fraud & AML Analytics in London employer: NTT America, Inc.
Contact Detail:
NTT America, Inc. Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Data Scientist – Fraud & AML Analytics in London
✨Tip Number 1
Network like a pro! Reach out to your connections in the industry, especially those who work in fraud detection or financial crime. A friendly chat can lead to insider info about job openings that aren't even advertised yet.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects in Python and PySpark. This is your chance to demonstrate how you've tackled real-world problems in fraud detection – make it shine!
✨Tip Number 3
Prepare for interviews by brushing up on your knowledge of Financial Crime domains. Be ready to discuss how your experience aligns with the role and share specific examples of how you've made an impact in previous positions.
✨Tip Number 4
Don't forget to apply through our website! We love seeing applications directly from candidates who are passionate about joining our team. It shows initiative and gives us a better sense of who you are.
We think you need these skills to ace Senior Data Scientist – Fraud & AML Analytics in London
Some tips for your application 🫡
Show Off Your Skills: Make sure to highlight your expertise in Python and PySpark right from the get-go. We want to see how your skills can help us tackle fraud detection and financial crime prevention.
Tailor Your Experience: Don’t just list your past jobs; connect your experience to the role. We’re looking for someone with 5+ years in relevant fields, so make it clear how your background fits into our needs.
Be Clear and Concise: Keep your application straightforward and to the point. We appreciate clarity, so avoid jargon unless it’s necessary to showcase your knowledge in Financial Crime domains.
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 don’t miss out on any important updates!
How to prepare for a job interview at NTT America, Inc.
✨Know Your Tech Inside Out
Make sure you brush up on your Python and PySpark skills. Be ready to discuss specific projects where you've used these technologies, especially in the context of fraud detection or financial crime prevention.
✨Understand Financial Crime Domains
Familiarise yourself with the latest trends and challenges in financial crime. Being able to speak knowledgeably about AML regulations and fraud detection techniques will show that you're not just a data whiz but also understand the industry.
✨Prepare for Scenario-Based Questions
Expect questions that ask how you would approach real-world problems. Think of examples from your past experience where you successfully tackled fraud-related issues using data analytics.
✨Show Your Flexibility
Since the role allows for remote or hybrid work, be prepared to discuss how you manage your time and collaborate effectively in different work environments. Highlight any previous remote work experience to demonstrate your adaptability.