Description
We are seeking an Integrated Financial Crime Machine Learning Engineer to join our team at Barclays. You will design, build, and deploy machine learning models that support scalable, high-quality financial crime detection across the bank.
The Integrated Financial Crime portfolio is a large-scale programme bringing together over 20 initiatives to create a more holistic, risk-based, and automated financial crime capability. The aim is to strengthen controls, improve effectiveness across all lines of defence, and better equip colleagues and customers to prevent and identify financial crime.
In this role, you will contribute across the full model lifecycle, from design and development through to deployment and optimisation. You will deliver new analytical solutions aligned to strategic priorities, while also maintaining and improving the robustness, accuracy, and performance of existing models.
Responsibilities
- Design analytics and modelling solutions to complex business problems using domain expertise.
- Collaborate with technology to specify dependencies required for analytical solutions, such as data, development environments, and tools.
- Develop high-performing, comprehensively documented analytics and modelling solutions, demonstrating their efficacy to business users and independent validation teams.
- Implement analytics and models in accurate, stable, well-tested software and work with technology to operationalise them.
- Provide 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.
Assistant Vice President Expectations
- Advise and influence decision-making, contribute to policy development, and take responsibility for operational effectiveness.
- Lead a team performing complex tasks, using well-developed professional knowledge and skills to deliver work that impacts the whole business function.
- Set objectives and coach employees in pursuit of those objectives, appraise performance relative to objectives, and determine reward outcomes.
Requirements
- Strong experience in machine learning and advanced analytics.
- Advanced Python skills for data processing and model development.
- Proven experience working with Databricks.
- Solid software engineering practices, including version control, testing, and deployment.
Nice to Have
- Background in financial services or regulated environments.
- Exposure to financial crime domains such as fraud, AML, or sanctions.
- Experience with Spark or PySpark.
- Familiarity with AWS cloud services and data platforms.
What We Offer
- Competitive salary.
- Opportunity to work on a large-scale programme to strengthen controls and improve effectiveness.
- Collaborative and dynamic work environment.