At a Glance
- Tasks: Design, build, and deploy scalable AI solutions for real-world applications.
- Company: Join a leading financial tech company shaping the future of AI in finance.
- Benefits: Competitive salary, comprehensive benefits, and career growth opportunities.
- Other info: Be part of a dynamic team focused on innovative AI products.
- Why this job: Make a real impact with cutting-edge AI technology in a collaborative environment.
- Qualifications: Expertise in NLP, Python, and experience with cloud platforms required.
The predicted salary is between 80000 - 100000 £ per year.
Requirements
- Extensive hands-on experience applying NLP and LLMs to real-world problems, with a consistent track record of shipping models to production and supporting them post-deployment.
- Strong Python programming skills, including object-oriented design and proficiency with key ML libraries (e.g., PyTorch, TensorFlow, Scikit-Learn).
- Solid understanding of probability and statistical modeling to support robust model development and interpretation.
- Experience with cloud platforms (especially Azure and/or AWS) and modern deployment practices for scalable AI delivery.
- Proven ability to set and uphold coding and model evaluation standards for production environments.
- Excellent communication skills to articulate technical decisions and trade-offs to both technical and non-technical audiences.
- Desirable: Familiarity with DevOps practices including CI/CD, version control, automated testing, and monitoring to support reliable model deployment and maintenance.
- Desirable: Experience with TypeScript, particularly for building or contributing to production services and APIs alongside ML systems.
EDUCATION
Bachelor's degree in Engineering, Computer Science, Data Science, Statistics, Mathematics, Physics or a related field, or equivalent practical experience.
What the job involves
ROLE SUMMARY: As a Principal Data Scientist (individual contributor), you will play a hands-on role in designing, building, and deploying scalable AI solutions that go beyond prototypes and are actively used in production. You’ll work closely with collaborative teams to co-develop innovative products for financial markets and professionals. We’re looking for someone who combines deep technical expertise in NLP and LLMs, strong Python engineering skills, and real-world experience shipping and supporting models in production. You should be comfortable owning delivery timelines and ensuring that solutions meet business needs and production-grade standards.
WHAT YOU’LL BE DOING: This is a hands-on technical leadership role in a high-impact environment focused on delivering production-ready AI systems. You will be part of the LSEG Workspace team — LSEG’s flagship platform that delivers personalised insights, news, and cutting-edge analytics to financial professionals worldwide. Your work will directly shape the AI capabilities embedded in a product that professionals rely on every day to make critical decisions.
- Lead the end-to-end development of AI solutions: design, build, test, and deploy models that are robust, scalable, and used by real users.
- Apply NLP and LLM techniques to solve real-world problems, ensuring models are optimised for performance and reliability.
- Continuously improve model quality through tuning, evaluation, and feedback from production usage.
- Evaluate third-party AI solutions with a critical eye on performance, scalability, and integration into production environments.
- Write and maintain production-grade Python code, adhering to best practices in software engineering and model development.
- Collaborate with engineering and business partners to define requirements, shape roadmaps, and ensure successful delivery of AI products.
High-impact projects: Work on innovative AI products that solve complex, high-value challenges using rich datasets.
Competitive benefits: Strong compensation, comprehensive benefits, and investment in your career growth.
Industry leadership: Be a founding member of a team delivering novel products that democratise modelling and analytics.
Collaborative environment: Join a team of experienced engineers in a culture of continuous learning and development.
Principal Applied Data Scientist employer: London Stock Exchange
At LSEG, we pride ourselves on being an exceptional employer, offering a dynamic work culture that fosters innovation and collaboration. As a Principal Applied Data Scientist, you will have the opportunity to lead high-impact projects in a supportive environment that values continuous learning and professional growth, all while enjoying competitive benefits and a commitment to your career development. Join us in shaping the future of AI solutions for financial professionals worldwide.
StudySmarter Expert Advice🤫
We think this is how you could land Principal Applied Data Scientist
✨Tip Number 1
Network like a pro! Reach out to folks in your industry on LinkedIn or at meetups. We all know that sometimes it’s not just what you know, but who you know that can help you land that Principal Applied Data Scientist role.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving NLP and LLMs. We want to see your hands-on experience, so make sure to highlight any models you've shipped to production.
✨Tip Number 3
Prepare for interviews by brushing up on your Python and ML libraries. We recommend practicing coding challenges and discussing your past projects. Be ready to explain your technical decisions clearly to both techies and non-techies!
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, we love seeing candidates who are proactive about their job search!
We think you need these skills to ace Principal Applied Data Scientist
Some tips for your application 🫡
Show Off Your Skills:Make sure to highlight your extensive hands-on experience with NLP and LLMs. We want to see how you've shipped models to production, so share specific examples that showcase your technical prowess!
Python is Key:Since strong Python programming skills are a must, don’t hold back! Mention your proficiency with key ML libraries like PyTorch and TensorFlow. We love seeing how you’ve applied these in real-world scenarios.
Cloud Experience Matters:If you've worked with cloud platforms like Azure or AWS, let us know! Share your experience with modern deployment practices, as this will show us you're ready for scalable AI delivery.
Communicate Clearly:Excellent communication skills are essential for this role. When writing your application, make sure to articulate your technical decisions and trade-offs clearly. We want to see how you can bridge the gap between technical and non-technical audiences!
How to prepare for a job interview at London Stock Exchange
✨Know Your NLP and LLMs
Make sure you brush up on your knowledge of Natural Language Processing and Large Language Models. Be ready to discuss specific projects where you've applied these techniques, including the challenges you faced and how you overcame them.
✨Showcase Your Python Skills
Prepare to demonstrate your Python programming prowess. Bring examples of your work with key ML libraries like PyTorch or TensorFlow, and be ready to explain your coding standards and practices in a production environment.
✨Understand Cloud Platforms
Familiarise yourself with Azure and AWS, as well as modern deployment practices. Be prepared to discuss how you've used these platforms to deliver scalable AI solutions and any relevant DevOps practices you've implemented.
✨Communicate Effectively
Practice articulating complex technical concepts in simple terms. You’ll need to convey your ideas clearly to both technical and non-technical audiences, so think of examples where you've successfully done this in the past.
