L

LSEG

Global financial market infrastructure and data

Associate Data Scientist

Applied Machine LearningPosted on Nov 11
Full-timeEdinburgh, UKNo salary listed

About the Job

Requirements

  • Knowledge of machine learning and generative AI concepts.
  • Understanding of statistical methods, experimentation, and data-driven decision making.
  • Ability to analyse data, identify patterns, and draw evidence-based conclusions.
  • Experience with Python or willingness to develop strong programming skills.
  • Ability to explain technical concepts clearly to diverse audiences.

Responsibilities

  • Contribute to AI-enabled products, services, and platforms, including large language model and agentic AI use cases.
  • Help develop tools, frameworks, and processes that improve how teams measure, monitor, and enhance AI capabilities.
  • Analyse data and communicate findings, recommendations, and trade-offs to technical and non-technical audiences.
  • Contribute to implementing solutions that are scalable, maintainable, and operationally robust.
  • Work with internal customers to understand quality requirements and translate them into measurable evaluation criteria.
  • Continuously develop expertise in AI evaluation, generative AI, prompt engineering, and emerging industry practices.

Desired Qualifications

  • Experience with AI evaluation, benchmarking, or experimentation methodologies.
  • Familiarity with large language models, prompt engineering, or agent-based AI systems.
  • Exposure to software engineering practices such as version control, testing, continuous integration/continuous delivery, or cloud platforms.

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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