Data Scientist

barclays; Glasgow; On-site; GBP 90,000 - 120,000; Full time

Job summary

Barclays is seeking a Data Scientist to extract insights from large data reserves and apply machine learning to drive strategic decisions and innovation. You will build predictive models, design complex analyses, and collaborate with senior stakeholders to realize commercial value.

The role emphasises production-grade Python development, scalable data pipelines, and advanced quantitative techniques across diverse data sources to inform risk and opportunity assessments.

Qualifications

• Experience in extracting insights from large data sets and presenting to non-technical stakeholders.
• Proficiency with statistical and ML methods including regression, clustering, NLP, and time-series analysis.
• Strong Python programming and production-grade software development skills.
• Experience with big data technologies and building data pipelines.

Responsibilities

• Identify, collect, and extract data from multiple sources.
• Clean, wrangle, and transform data for analysis and modeling.
• Develop and maintain efficient data pipelines for automated processing.
• Design and implement statistical and ML models to analyze patterns and trends.
• Develop predictive models to forecast outcomes and assess risks and opportunities.
• Collaborate with business stakeholders to translate data insights into value.

Skills

Strategic insights

Python

Machine learning

Statistics

Data wrangling

Communication

Big data technologies

Production-grade code

Tools

Pandas

NumPy

scikit-learn

TensorFlow

Job description

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 effectiveness. Collaborate closely with other functions/ business divisions. Lead a team performing complex tasks, using well developed professional knowledge and skills to deliver on work that impacts the whole business function. Set objectives and coach employees in pursuit of those objectives, appraisal of performance relative to objectives and determination of reward outcomes. If the position has leadership responsibilities, People Leaders are expected to demonstrate a clear set of leadership behaviours to create an environment for colleagues to thrive and deliver to a consistently excellent standard. The four LEAD behaviours are: L - Listen and be authentic, E - Energise and inspire, A - Align across the enterprise, D - Develop others. OR for an individual contributor, they will lead collaborative assignments and guide team members through structured assignments, identify the need for the inclusion of other areas of specialisation to complete assignments. They will identify new directions for assignments and/ or projects, identifying a combination of cross functional methodologies or practices to meet required outcomes. Consult on complex issues; providing advice to People Leaders to support the resolution of escalated issues. Identify ways to mitigate risk and developing new policies/procedures in support of the control and governance agenda. Take ownership for managing risk and strengthening controls in relation to the work done. Perform work that is closely related to that of other areas, which requires understanding of how areas coordinate and contribute to the achievement of the objectives of the organisation sub-function. Collaborate with other areas of work, for business aligned support areas to keep up to speed with business activity and the business strategy. Engage in complex analysis of data from multiple sources of information, internal and external sources such as procedures and practises (in other areas, teams, companies, etc).to solve problems creatively and effectively. Communicate complex information. 'Complex' information could include sensitive information or information that is difficult to communicate because of its content or its audience. Influence or convince stakeholders to achieve outcomes.

All colleagues will be expected to demonstrate the Barclays Values of Respect, Integrity, Service, Excellence and Stewardship - our moral compass, helping us do what we believe is right. They will also be expected to demonstrate the Barclays Mindset - to Empower, Challenge and Drive - the operating manual for how we behave.

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 wit