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- Tasks: Lead AI innovation in fraud prevention using Large Language Models and advanced Machine Learning.
- Company: Global tech and data analytics leader with a focus on innovation.
- Benefits: Remote work, competitive salary, and opportunities for professional growth.
- Other info: Join a dynamic team dedicated to driving AI advancements.
- Why this job: Make a real impact on global fraud prevention while working with cutting-edge technology.
- Qualifications: Strong Python skills, deep learning experience, and a collaborative mindset.
The predicted salary is between 48000 - 72000 £ per year.
A leading global technology and data analytics firm is seeking a Principal Data Scientist to drive AI innovation within their Fraud and Identity portfolio. The ideal candidate will lead research and model implementation, focusing on Large Language Models and advanced Machine Learning techniques. This remote role requires strong Python skills, experience in deep learning, and a collaborative mindset. Join us to make a significant impact on fraud prevention globally.
Principal AI Scientist: Fraud & Identity (LLMs) employer: LexisNexis Risk Solutions
Contact Detail:
LexisNexis Risk Solutions Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Principal AI Scientist: Fraud & Identity (LLMs)
✨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! Create a portfolio showcasing your projects, especially those involving Large Language Models and deep learning. This is your chance to shine!
✨Tip Number 3
Prepare for interviews by brushing up on your Python skills and understanding the latest trends in AI. We want you to feel confident and ready to impress!
✨Tip Number 4
Don't forget to apply through our website! It’s the best way to ensure your application gets noticed. Plus, we love seeing candidates who are proactive!
We think you need these skills to ace Principal AI Scientist: Fraud & Identity (LLMs)
Some tips for your application 🫡
Show Off Your Skills: Make sure to highlight your Python expertise and experience with deep learning in your application. We want to see how your skills align with the role of Principal AI Scientist, so don’t hold back!
Tailor Your Application: Customise your CV and cover letter to reflect the specific requirements mentioned in the job description. We love seeing candidates who take the time to connect their experience with our needs in fraud prevention and identity management.
Be Collaborative: Since this role requires a collaborative mindset, share examples of how you've worked effectively in teams. We’re looking for someone who can lead but also work well with others, so let that shine through!
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 this exciting opportunity to drive AI innovation with us!
How to prepare for a job interview at LexisNexis Risk Solutions
✨Know Your LLMs
Make sure you brush up on your knowledge of Large Language Models. Be prepared to discuss their applications in fraud detection and identity verification, as well as any recent advancements in the field. This shows your passion and expertise.
✨Showcase Your Python Skills
Since strong Python skills are a must, be ready to demonstrate your coding abilities. You might be asked to solve a problem or explain your approach to a project. Practise coding challenges related to data science and machine learning to feel confident.
✨Collaborative Mindset is Key
This role requires a collaborative approach, so think of examples where you've successfully worked in teams. Be ready to share how you’ve contributed to group projects, especially in AI or data science contexts, to highlight your teamwork skills.
✨Impact on Fraud Prevention
Prepare to discuss how your work can make a difference in fraud prevention. Think about specific strategies or models you would implement and how they could improve existing systems. This will show your understanding of the role's significance.