About the Role
This is a rare opportunity to join a new Quant AI/ML team within QA, focused on developing cutting-edge generative AI applications that will transform how risk and finance functions operate. You’ll work on high-impact projects—from payment systems to credit and finance use cases—while shaping the bank’s approach to large language models, vector databases, and next-generation AI tooling. If you’re excited by innovation, hands-on model development, and the chance to influence a greenfield capability, this role offers an exceptional platform to grow.
Purpose of the role
To design, develop, implement, and support mathematical, statistical, and machine learning models and analytics used in business decision-making.
Accountabilities
- 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 operationalise 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.
Vice President Expectations
- Contribute to or set strategy, drive requirements and make recommendations for change. Plan resources, budgets, and policies; manage and maintain policies/processes; deliver continuous improvements and escalate breaches of policies/procedures.
- If managing a team, define jobs and responsibilities, planning for the department’s future needs and operations, counselling employees on performance and contributing to employee pay decisions/changes. They may also lead a number of specialists to influence the operations of a department, in alignment with strategic as well as tactical priorities, while balancing short and long term goals and ensuring that budgets and schedules meet corporate requirements.
- OR for an individual contributor, they will be a subject matter expert within own discipline and will guide technical direction. They will lead collaborative, multi-year assignments and guide team members through structured assignments, identify the need for the inclusion of other areas of specialisation to complete assignments. They will train, guide and coach less experienced specialists and provide information affecting long term profits, organisational risks and strategic decisions.
- Advise key stakeholders, including functional leadership teams and senior management on functional and cross functional areas of impact and alignment.
- Manage and mitigate risks through assessment, in support of the control and governance agenda.
- Demonstrate leadership and accountability for managing risk and strengthening controls in relation to the work your team does.
- Demonstrate comprehensive understanding of the organisation functions to contribute to achieving the goals of the business.
- Collaborate with other areas of work, for business aligned support areas to keep up to speed with business activity and the business strategies.
- Create solutions based on sophisticated analytical thought comparing and selecting complex alternatives. In-depth analysis with interpretative thinking will be required to define problems and develop innovative solutions.
- Adopt and include the outcomes of extensive research in problem solving processes.
- Seek out, build and maintain trusting relationships and partnerships with internal and external stakeholders in order to accomplish key business objectives, using influencing and negotiating skills to achieve outcomes.
Requirements
To be successful as a Quant AI/ML Model Developer, you should have experience with:
- Python programming and implementing AI/ML models, ideally including generative AI.
- Working with large language models, prompt engineering, RAG pipelines, or vector databases.
- Applying quantitative or technical skills gained through a relevant degree (e.g., computer science, maths, physics).
- Understanding of the GenAI landscape, including model options, implementation details, and platforms such as Bedrock.
- Familiarity with financial services or experience working in a banking environment.
- Strong communication skills to simplify complex technical concepts for diverse stakeholders.