Lead Data Scientist
LSEG’s data-science team builds AI for financial-data workflows. The role develops extraction, modelling and evaluation systems for financial analytics.
What you’d work on
Our reading of the posting: what a new hire in this role would most likely spend their first months on.
- Develop financial-data AI workflows.
- Evaluate NLP and retrieval models.
- Deploy and monitor analytical services.
What they ask for
Required
- Python
- Statistics
- NLP and LLMs
- Cloud delivery
- Model evaluation
Preferred
- Financial-services experience
- Education
- Relevant master’s study or engineering degree specialising in data science/AI.
- Experience
- Eight to twelve years in data science or AI.
- Languages and tools
How to prepare
- Evaluate extracted financial entities.
- Test a retrieval-based analysis.
- Monitor drift and failure cases.
What to study
The NLP and ML Quant Researcher roadmap sets out the stages for this kind of role, with free resources for each.
Open the roadmapApply
Read the full posting on London Stock Exchange Group’s site before applying: requirements, location and pay can change after we check them.
View the posting on London Stock Exchange Group’s site ↗
SelfMadeQuant wrote this summary from the employer’s public posting, last checked 6 November 2026. SelfMadeQuant isn’t affiliated with London Stock Exchange Group and doesn’t handle applications.