Location
Paternoster Square, London

Hours
Full Time

Salary
Negotiable

About the Role
London Stock Exchange Group (LSEG) is a leading global financial markets infrastructure and data provider with a 300-year legacy of supporting financial stability and economic growth worldwide. We are seeking an experienced Data Scientist to develop and deploy enterprise-scale AI and machine learning solutions that enhance operational efficiency, service resilience and customer outcomes. You will collaborate 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 to production. This role requires a blend of strong technical expertise, commercial awareness and the ability to translate complex data into actionable insights that deliver measurable business value. You will contribute to AI product roadmaps, promote responsible AI practices and help grow LSEG's AI and Data Science community through knowledge sharing and mentoring. Join us to be part of a dynamic organisation that values innovation, diversity and continuous improvement, enabling you to grow and fulfil your potential in a meaningful career.

Experience
Proven experience delivering machine learning or AI solutions in large-scale enterprise environments. Strong background in statistical modelling, predictive analytics and experimentation techniques. Skilled in working with structured and unstructured data at scale. Demonstrated ability to translate business problems into measurable analytical outcomes. Experience deploying models into production environments.

About you
Strong problem-solving and analytical thinking skills. Passionate about applying AI to real-world challenges. Customer-focused with a results-oriented mindset. Effective collaborator able to work across organisational boundaries. Ownership and accountability for delivery. Excellent communication and stakeholder management skills. Commitment to continuous learning and innovation.

Qualifications
Technical proficiency in Python and its data science ecosystem (Pandas, NumPy, Scikit-learn). Familiarity with machine learning techniques including classification, regression, clustering and anomaly detection. Experience with Generative AI, large language models (LLMs), retrieval-augmented generation (RAG) architectures or agent-based AI solutions. Strong SQL skills and experience with large-scale data analysis. Knowledge of cloud-based data science platforms and MLOps practices. Competence in data visualisation and storytelling tools. Desirable: experience in financial services or regulated environments, familiarity with Azure AI services, observability or operational analytics, AI-powered automation, and Responsible AI/model governance frameworks.