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- Tasks: Design and operate AI-driven solutions while analysing production data.
- Company: Global financial markets infrastructure company with a focus on innovation.
- Benefits: Competitive salary, flexible work options, and opportunities for professional growth.
- Why this job: Influence AI practices in an industry-leading organisation and work on exciting projects.
- Qualifications: Strong programming skills in Python and experience with data manipulation.
- Other info: Join a dynamic team and shape the future of AI in finance.
The predicted salary is between 36000 - 60000 £ per year.
A global financial markets infrastructure company is seeking an experienced Data Scientist to establish its first LLM Ops capability. The candidate will design and operate AI-driven solutions while collaborating with cross-functional teams.
Key responsibilities include:
- Analyzing production data
- Managing AI models
- Developing scalable code
Ideal candidates should have strong programming skills in Python and experience with data manipulation and governance practices. This exciting role offers the opportunity to influence AI practices within an industry-leading organization.
Production AI & LLM Ops Data Scientist employer: LSEG
Contact Detail:
LSEG Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Production AI & LLM Ops Data Scientist
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, especially those working in AI and data science. 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, especially those involving Python and AI models. This gives potential employers a taste of what you can do and sets you apart from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and soft skills. Practice explaining complex concepts in simple terms, as you'll need to collaborate with cross-functional teams.
✨Tip Number 4
Don't forget to apply through our website! We love seeing applications directly from candidates who are excited about joining us. It shows initiative and helps us get to know you better.
We think you need these skills to ace Production AI & LLM Ops Data Scientist
Some tips for your application 🫡
Show Off Your Skills: Make sure to highlight your programming skills in Python and any experience you have with data manipulation. We want to see how you can bring your expertise to the table, so don’t hold back!
Tailor Your Application: Take a moment to customise your application for this role. Mention specific projects or experiences that relate to AI-driven solutions and LLM Ops. This shows us you’re genuinely interested and have done your homework.
Be Clear and Concise: When writing your application, keep it clear and to the point. We appreciate well-structured responses that get straight to the heart of your experience and how it aligns with our needs.
Apply Through Our Website: Don’t forget to apply through our website! It’s the best way for us to receive your application and ensures you’re considered for this exciting opportunity in our team.
How to prepare for a job interview at LSEG
✨Know Your AI and LLM Basics
Make sure you brush up on your knowledge of AI-driven solutions and LLM Ops. Be ready to discuss how you've applied these concepts in previous roles, as well as any challenges you've faced and how you overcame them.
✨Show Off Your Python Skills
Since strong programming skills in Python are a must, prepare to demonstrate your coding abilities. You might be asked to solve a problem on the spot, so practice common data manipulation tasks and be ready to explain your thought process.
✨Understand Data Governance
Familiarise yourself with data governance practices, as this role involves managing production data. Be prepared to discuss how you've ensured data quality and compliance in past projects, and share examples of how you've handled data-related challenges.
✨Collaborate Like a Pro
This position requires collaboration with cross-functional teams, so think of examples where you've successfully worked with others. Highlight your communication skills and how you’ve contributed to team success in previous roles.
