Data Scientist

Join our team as a Data Scientist, where you will develop and deploy enterprise-scale AI and machine learning solutions to improve operational efficiency, service resilience, and customer outcomes. You will work closely with various teams to identify opportunities, build predictive models, and take products from concept to production. Your responsibilities will include designing and deploying machine learning models, developing predictive analytics capabilities, evaluating emerging AI technologies, and creating insights for decision-making. The ideal candidate will have strong technical expertise, experience in delivering machine learning solutions, and a customer-focused mindset.

- Design, build and deploy machine learning models to solve operational and business challenges, and develop predictive analytics capabilities. - Evaluate emerging AI technologies and recommend practical applications across the organization, and support the development of Generative AI applications. - Communicate technical concepts clearly to both technical and non-technical audiences, and contribute to the growth of LSEG's AI and Data Science community through knowledge sharing and mentoring.

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