Data Scientist; Machine Learning

In your role as Data Scientist (Machine Learning), you will design and build machine learning solutions that strengthen the bank’s ability to detect financial crime, prevent fraud, and safeguard customers. Working within an established model development team and alongside business stakeholders and engineers, your role focuses on the development of robust and intuitive machine learning model solutions, delivered via scalable, production-grade code, accompanied by comprehensive monitoring and controls.

You will support the full model lifecycle—from inception and data exploration through supporting model deployment—while adhering to rigorous documentation and governance practices as required in a regulated environment. This position is designed for early-career data scientists with a good academic foundation who are passionate about applying machine learning to real-world fraud and financial crime challenges.

To be successful in your role as Data Scientist (Machine Learning) you should have:

• An academic background in quantitative or computational discipline (mathematics, statistics, computer science, engineering, or related fields) with exposure to machine learning concepts.
• Practical coding ability in Python and familiarity with machine learning libraries and distributed data frameworks.
• Considerable understanding of core principles in machine learning, statistical modelling, data analysis, and algorithmic thinking.

Other highly valued skills include:

• Exposure to aspects of model development (data preparation, development, deployment, monitoring).
• Familiarity with cloud platforms (AWS, Azure, or GCP) or ML-focused services (e.g. Databricks).
• Keen interest in Dev Ops/MLOps fundamentals—version control (Git), unit testing, CI/CD pipelines, modular code design.
• Awareness of model risk management, governance, and controls within the financial services’ regulatory environment.

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, digital and technology, as well as job‑specific technical skills.

This role is located in Wilmington, DE.

To design, develop, implement, and support mathematical, statistical, and machine learning models and analytics used in business decision-making.

• Design analytics and modelling solutions to complex business problems using domain expertise.
• Collaboration with technology to specify any dependencies required for analytical solutions, such as data, development environments and tools.
• Development of high performing, comprehensively documented analytics and modelling solutions, demonstrating their efficacy to business users and independent validation teams.
• Implementation of analytics and models in accurate, stable, well‑tested software and work with technology to ope rationalise them.
• Provision of ongoing support for the continued effectiveness of analytics and modelling solutions to users.
  
  Demonstrate conformance to all Barclays Enterprise Risk Management Policies, particularly Model Risk Policy.
• Ensure all development activities are undertaken within the defined control environment.

• To perform prescribed activities in a timely manner and to a high standard consistently driving continuous improvement.
• Requires in-depth technical knowledge and experience in their assigned area of expertise.
• Thorough understanding of the underlying principles and concepts within the area of expertise.
• They lead and supervise a team, guiding and supporting professional development, allocating work requirements and coordinating team resources.
• 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 develop technical expertise in work area, acting as an advisor where appropriate.
• Will have an impact on the…