Data Scientist, London Stock Exchange

• The ideal candidate combines strong technical expertise with commercial awareness and the ability to translate complex data into actionable insights and measurable business value
• Demonstrable experience delivering machine learning or AI solutions within a large-scale enterprise environment
• Strong experience applying statistical modelling, predictive analytics and experimentation techniques
• Experience working with structured and unstructured data at scale
• Proven ability to translate business problems into measurable analytical outcomes
• Experience taking models from development into production environments
• Python and associated data science ecosystem (Pandas, NumPy, Scikit-learn)
• Machine learning techniques including classification, regression, clustering and anomaly detection
• Experience with Generative AI, LLMs, RAG architectures or agent-based AI solutions
• SQL and large-scale data analysis
• Cloud-based data science platforms and MLOps practices
• Data visualisation and storytelling tools
• Strong problem-solving capability and analytical thinking
• Curiosity and a passion for applying AI to real-world challenges
• Customer-focused mindset with a focus on outcomes
• Ability to work effectively across organisational boundaries
• Ownership and accountability for delivery
• Clear communication and stakeholder management skills
• Commitment to continuous learning and innovation

Desirable

• We are seeking an experienced Data Scientist to help develop and deploy enterprise-scale AI and machine learning solutions that improve operational efficiency, service resilience and customer outcomes
• You will work closely with software engineers, SREs, product managers, platform teams and business stakeholders to identify opportunities, build predictive models, evaluate AI solutions and take products from concept through to production
• Design, build and deploy machine learning models to solve operational and business challenges
• Develop predictive analytics capabilities focused on incident prevention, service health, operational risk and customer experience
• Support the development of Generative AI applications leveraging LLMs, retrieval systems and agentic workflows
• Evaluate emerging AI technologies and recommend practical applications across the organisation
• Perform advanced statistical analysis and modelling across large-scale operational and engineering datasets
• Develop feature engineering, experimentation and model evaluation frameworks
• Create insights and recommendations that drive decision making for senior stakeholders
• Build and maintain reproducible data science workflows and pipelines
• Partner with engineering and product teams to transition solutions from proof-of-concept into production
• Define success metrics and measurement frameworks for AI products
• Support model monitoring, governance and continuous improvement activities
• Contribute to AI product roadmaps and prioritisation discussions
• Work with subject matter experts from Engineering, Operations, Service Management and Product organisations
• Communicate technical concepts clearly to both technical and non-technical audiences
• Contribute to the growth of LSEG's AI and Data Science community through knowledge sharing and mentoring
• Promote responsible AI, model governance and data-driven decision making