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- Tasks: Lead the development of scalable AI solutions and deploy impactful models.
- Company: Global leader in financial markets with a focus on innovation.
- Benefits: Flexible work arrangements, robust benefits package, and continuous learning opportunities.
- Why this job: Make a real impact with AI while working on high-stakes projects.
- Qualifications: Extensive data science experience, strong Python skills, and cloud tech expertise.
- Other info: Collaborative culture that values growth and innovation.
The predicted salary is between 54000 - 84000 £ per year.
A leading global financial markets provider is seeking a Principal Data Scientist to lead the development of scalable AI solutions. The role requires extensive experience in data science, particularly in deploying AI models, with strong programming skills in Python and expertise in cloud technologies like Azure or AWS.
Candidates will have the opportunity to work on high-impact projects, leverage extensive datasets, and enjoy a robust benefits package, including flexible work arrangements. The team values continuous learning and a collaborative work culture.
Lead Applied AI Scientist, Production Systems in City of London employer: LSEG
Contact Detail:
LSEG Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Lead Applied AI Scientist, Production Systems in City of London
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend meetups, and connect on LinkedIn. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your AI projects, especially those involving Python and cloud technologies. This will give potential employers a taste of what you can bring to the table.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and soft skills. Practice common data science interview questions and be ready to discuss your past projects and how they relate to scalable AI solutions.
✨Tip Number 4
Don’t forget to apply through our website! We’ve got loads of opportunities that might just be the perfect fit for you. Plus, it’s a great way to get noticed by our hiring team.
We think you need these skills to ace Lead Applied AI Scientist, Production Systems in City of London
Some tips for your application 🫡
Showcase Your Experience: Make sure to highlight your extensive experience in data science and deploying AI models. We want to see how your skills in Python and cloud technologies like Azure or AWS can contribute to our high-impact projects.
Tailor Your Application: Don’t just send a generic application! Tailor your CV and cover letter to reflect the specific requirements of the Lead Applied AI Scientist role. We love seeing candidates who take the time to connect their experiences with what we’re looking for.
Highlight Collaborative Spirit: Since we value a collaborative work culture, share examples of how you’ve worked effectively in teams. Let us know how you’ve contributed to a positive team environment and continuous learning in your previous roles.
Apply Through Our Website: We encourage you to apply through our website for a smoother process. It’s the best way for us to receive your application and ensure it gets the attention it deserves!
How to prepare for a job interview at LSEG
✨Know Your AI Models Inside Out
Make sure you can discuss the AI models you've deployed in detail. Be ready to explain your thought process, the challenges you faced, and how you overcame them. This shows your depth of knowledge and practical experience.
✨Showcase Your Programming Skills
Brush up on your Python skills before the interview. Be prepared to solve coding problems or discuss your previous projects where you used Python. Highlight any specific libraries or frameworks you’re familiar with that are relevant to AI.
✨Familiarise Yourself with Cloud Technologies
Since the role requires expertise in Azure or AWS, make sure you understand the key features and services of these platforms. Be ready to discuss how you've used cloud technologies in your past projects to deploy AI solutions.
✨Emphasise Collaboration and Continuous Learning
The team values a collaborative culture, so be prepared to share examples of how you've worked effectively in teams. Also, mention any recent learning experiences or courses you've taken to stay updated in the field of data science and AI.
