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Data Scientist

Job in Glasgow, Glasgow City Area, G1, Scotland, UK
Listing for: Barclays
Full Time position
Listed on 2026-03-01
Job specializations:
  • IT/Tech
    Data Scientist, Data Analyst, Machine Learning/ ML Engineer, Data Engineer
Job Description & How to Apply Below

Join us as a Data Scientist and work closely with senior business stakeholders, uncover, shape and deliver data science projects that enable the realisation of significant (£m) commercial value, Generate sound actionable strategic insights from enormous amounts of raw data through the intelligent application of a broad range of advanced quantitative analytical and statistical techniques from fields such as statistic pattern recognition, machine learning, multivariate data analysis and systems dynamics.

You will design, build and test complex business and customer behaviour forecasting models and perform scenario simulations.

Key Skills
  • Exceptional ability to extract strategic insights from large data sets and communicate these to non-technical business stakeholders
  • Experience with multiple of the following methods: PCA, MDS, factor analysis, regression analysis, choice models, cluster analysis, density estimation, kernel methods, Bayesian methods, classification, decision trees, MCMC, systems dynamics, gradient boosting, NLP
  • Significant experience applying machine learning methods with big data technologies.
  • Significant experience in Python and the key analytical and machine learning libraries. Able to write production quality code with strong grasp of key coding principles: e.g. separation of concerns, generalisation of code.
  • Experience on building and deploying in cloud infrastructure such as AWS, Azure or GCP
  • Experience in leading on, building and deploying enterprise GenAI projects,
  • Deep understanding of LLMs, GenAI frameworks and techniques e.g. RAG, Agentic AI, evaluation and monitoring
  • Ability to understand and translate the pattern recognition, exploration of the data, machine learning and algorithmic learning
  • Actively seeks out and applies new analytical methods that can improve the speed and quality of the decision takes within Barclays Business
  • Experience in providing technical mentoring to more junior colleagues
Desirable skills
  • Masters or PhD in a highly numerate discipline such Statistics, Mathematics, Physics, Computer Science or Engineering with a strong programming background
  • Experienced in creating business models, both financial and consumer behavioural
  • Extensive experience of statistical analysis, data mining and visualisation techniques
Additional Experience
  • Experience of data warehouse and MI environments and practises with good working knowledge of SQL and at least one business intelligence package (Tableau/Power

    BI)
  • Experience in PySpark and a Hadoop environment
  • Project management and cross functional matrix leadership experience
  • Experience in line management of data scientists
  • Experience in front end development frameworks such as Angular/React/ Flask/Streamlit
  • Modular code frameworks e.g MVC Architecture

You may be assessed on the key critical skills relevant for success in role, such as risk and controls, change and transformation, business acumen strategic thinking and digital and technology, as well as job-specific technical skills.

This role will be based in Glasgow or London.

Purpose of the role

To use innovative data analytics and machine learning techniques to extract valuable insights from the bank's data reserves, leveraging these insights to inform strategic decision-making, improve operational efficiency, and drive innovation across the organisation.

Accountabilities
  • Identification, collection, extraction of data from various sources, including internal and external sources.
  • Performing data cleaning, wrangling, and transformation to ensure its quality and suitability for analysis.
  • Development and maintenance of efficient data pipelines for automated data acquisition and processing.
  • Design and conduct of statistical and machine learning models to analyse patterns, trends, and relationships in the data.
  • Development and implementation of predictive models to forecast future outcomes and identify potential risks and opportunities.
  • Collaborate with business stakeholders to seek out opportunities to add value from data through Data Science.
Assistant Vice President Expectations
  • To advise and influence decision making, contribute to policy development and take responsibility for operational…
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