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Key skills for this role
Develop, validate, and implement credit risk and machine learning models to support credit risk assessment, fraud detection, impairment provisioning and capital adequacy.
Analyse large and complex datasets from multiple sources (structured and unstructured) to identify patterns, drivers, and emerging risks.
Apply predictive modelling and AI techniques to optimise customer decisioning strategies and risk-based pricing.
Evaluate data sources, governance, and quality to ensure reliability and compliance with regulatory standards.
Work with cloud-based and on-premise data solutions to deliver scalable analytics.
Partner with Risk, Finance, Product, and Technology colleagues to translate business problems into data science solutions.
Communicate complex findings to non-technical stakeholders through clear storytelling, dashboards, and visualisations.
Present insights and recommendations to senior stakeholders to guide strategic decision-making.
Stay at the forefront of emerging data science techniques, tools, and regulatory developments affecting financial services.
Contribute to the development of Shawbrook’s decision science capability, embedding AI and automation into risk processes.
Support ongoing model monitoring, back-testing, and recalibration to maintain model performance.
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Curious and Analytical – seeks to uncover new insights and challenge existing assumptions. Creative in how they approach problems
Collaborative – works effectively across multi-disciplinary teams.
Commercially Minded – balances technical rigour with practical business impact.
Adaptable – thrives in a dynamic environment with shifting priorities. Able to prioritise workload and tasks.
Communication - articulate, both verbally and in the way that information is conveyed in reports and presentations, with ability to communicate complex information in a simple and effective way.
Be part of a fast-growing specialist bank, leveraging data and decision science to transform risk management.
Opportunity to apply cutting-edge techniques in AI, machine learning, and advanced analytics.
Join a collaborative culture where curiosity, innovation, and impact are encouraged.
Support to continue developing your technical and professional skills, with pathways for further qualifications and advancement.
104 UCAS points (BCC at A Level) and GCSE Mathematics and English (grade C/4 or above).
Completion of a Level 3 Apprenticeship/Professional Qualification in a relevant discipline
We will consider applications from employees with 1-2 years work experience, ideally within banking, financial services, or fintech.
Your Wellbeing - We take your health and well-being very seriously by providing a range of benefits to give you and your family peace of mind. These include:
Market leading family friendly policies such as access to our Maternity, Adoption and Paternity policies from Day 1 of your employment
Free access to Headspace, a mindfulness & meditation digital health app
Free access to Peppy digital health app that offers personalised support through fertility treatment becoming a parent or menopause
EAP (Employee Assistance Programme) - Offering you support on a wide range of subjects including financial concerns, mental wellbeing and more general queries around family, work, housing, and health
Cycle to work scheme
Discounts on gym membership
Contributory pension scheme & death in service
Your Lifestyle - It’s important you strike the right balance between your work and personal life. We provide benefits to support you when at work and when you’re enjoying your leisure time.
Minimum of 27 days holiday per year
Option to buy or sell holiday days through our flexi-holiday scheme
Discounts on gym membership nationwide
Access to discounts on a range of high street and online brands
Community support and charitable giving
Your Contribution - We’re focused on rewarding those that go the extra mile in helping us achieve our goals.
Participation in our annual discretionary bonus scheme designed to reward your contribution to our success
Proudly Shawbrook recognition scheme focused on recognising our role models and thanking our colleagues for a job well done
Verified company details for this employer are not available yet.
Full Time, Internship
Entry · 1+ years experience
Hybrid
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