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LSEG

Global financial market infrastructure and data

Data Scientist

Applied Machine LearningConfirmed live in the last 24 hours
Full-timeLondon, UKNo salary listedIn-person

About the Job

Requirements

  • Demonstrable experience delivering machine learning or artificial intelligence 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.
  • Proficiency in Python and its data science ecosystem, including Pandas, NumPy, and Scikit-learn.
  • Knowledge of machine learning techniques including classification, regression, clustering, and anomaly detection.
  • Experience with Generative AI, large language models, retrieval-augmented generation architectures, or agent-based AI solutions.
  • Experience with SQL and large-scale data analysis.
  • Experience with cloud-based data science platforms and MLOps practices.
  • Experience with data visualisation and storytelling tools.

Responsibilities

  • 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 development of Generative AI applications using large language models, 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 support decision making by 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 to technical and non-technical audiences.
  • Contribute to the growth of the organisation's AI and Data Science community through knowledge sharing and mentoring.
  • Promote responsible AI, model governance, and data-driven decision making.

Desired Qualifications

  • Experience within financial services, regulated environments, or market infrastructure.
  • Familiarity with Azure AI services and the Microsoft AI ecosystem.
  • Experience with observability, SRE, or operational analytics use cases.
  • Experience developing AI-powered automation solutions.
  • Knowledge of Responsible AI and model governance frameworks.

About the Company

LSEG

Global financial market infrastructure and data

LSEG provides global financial market infrastructure and data across the full value chain. It delivers data, analytics, and risk-management tools, benchmarks via FTSE Russell, regulatory and financial crime risk services, and trading, clearing, and settlement through its Capital Markets and Post Trade divisions, typically accessed via subscriptions, licensing, and fees. The company differentiates itself by offering an integrated, end-to-end platform that covers pre-trade data and analytics to post-trade processing with a broad, global footprint. Its goal is to grow over the long term by leveraging its diversified portfolio and international reach to create value for shareholders and customers.

Company size
10,001+
Company stage
IPO
Headquarters
London, United Kingdom
Founded
1801

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