Data Scientist

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

• 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.

Essential Skills/Basic Qualifications: 

• Bachelor or masters degree in data science (or similar) or equivalent commercial experience 

• Commercial experience in applying machine learning techniques to generate business value (e.g.  clustering, classification, regression, NLP techniques) – interest/experience in deep learning is beneficial. 

• Ability to write close to production standard code with strong understanding of key coding principals e.g. separation of concerns, generalisation of code. Strong experience in Python and SQL is a must. 

• Ability to translate technical work into business terms and communicate value to business stakeholders. 

• Knowledge of code management methodologies and ability to implement these on projects. 

• Comfortable working with AWS data science services including Sagemaker 

• Experience of working in a big data environment using PySpark 

• Experience in a data visualisation software (Tableau – preferable /Qlikview/PowerBI or similar)