Fraud Strategy and Analytics Analyst
Industry: Investment Banking
Location: London
Role Type: Permanent
Work Setup: Onsite
Who We Are
We are a consultancy operating within Robert Walters, the world's most trusted talent solutions business. Across the globe, we deliver recruitment, outsourcing, and talent advisory services for businesses of all sizes, opening doors for people with diverse skills, ambitions, and backgrounds.
The Role
We have an exciting new opportunity for a Fraud Strategy and Analytics Analyst to join Robert Walters as a Consultant where you will benefit from permanent employment with Robert Walters and will be deployed on an assignment with one of our clients, a leading US Investment Bank. In return, we will provide you with the opportunity to develop your skills with ongoing training and professional support.
This role sits at the intersection of fraud strategy and data analytics, supporting the development and optimisation of fraud strategies to manage losses, improve fraud prevention and enhance customer outcomes.
The successful candidate will have a minimum of 3+ years experience working in fraud, ideally within a UK or European bank, combined with strong data analytics skills. You will use data to understand fraud trends and losses, investigate the root causes of issues and develop analytical solutions that support effective fraud strategies and rules.
You will work closely with Fraud, Operations, Product and Modelling teams, translating data and analysis into practical recommendations and improvements to fraud strategy.
Key Responsibilities
- Analyse fraud losses, trends, customer behaviour and strategy performance to identify emerging risks, root causes and opportunities for improvement.
- Support the development, enhancement and optimisation of fraud strategies, rules and processes within relevant risk, control, compliance and regulatory frameworks.
- Use SQL and Python to investigate fraud-related issues, analyse large datasets, identify trends and develop analytical solutions to support decision-making.
- Understand data flows across systems and processes, identifying appropriate data sources to answer fraud, customer and business-related questions.
- Build and maintain dashboards and reporting that monitor fraud losses, trends, customer impact and the effectiveness of fraud strategies.
- Investigate changes in fraud performance and recommend clear, actionable responses to technical and non-technical stakeholders.
- Collaborate with Fraud, Operations, Product and Modelling teams to implement effective fraud solutions, improve analytical capabilities and maintain awareness of UK and European banking trends and best practice.
Required Experience and Skills
- Minimum of three years' experience in fraud analytics, fraud operations or fraud risk, ideally within a UK or European bank or other financial services organisation.
- Experience working with fraud losses, fraud strategies, fraud rules, fraud controls and related performance metrics.
- Strong analytical and problem-solving skills, with the ability to identify trends, anomalies, root causes and actionable insights from data.
- Advanced SQL and Python skills, with experience analysing large, complex datasets and developing analytical solutions.
- Strong Excel skills, with practical experience producing analysis, MI, dashboards and data visualisations.
- Good understanding of data flows, data sources and data structures, with the ability to identify and use appropriate data to solve business problems.
- Excellent stakeholder management and communication skills, including the ability to work collaboratively with Fraud, Operations, Product and Modelling/Analytics teams and present findings clearly to varied audiences.
Desirable Skills
- Experience with Looker.
- Experience with Git/GitHub or similar version control tools.
- Experience working with banking, payments or other financial services data.
Looker and GitHub are desirable rather than essential and can be learned in the role.
Important
This is a fraud strategy and data analytics role, rather than a pure data science or engineering position. Machine learning modelling and data engineering experience are not required.
The ideal candidate will be able to take a fraud problem, understand the underlying data, investigate the root cause using SQL and Python, and turn the analysis into practical recommendations for improving fraud strategy and managing fraud losses.
What's Next
If you are ready to take the next step, apply now! Successful applicants will be contacted directly by a recruiter to discuss the role more.
We are committed to creating an inclusive recruitment experience. If you require support or adjustments to the recruitment process, our Adjustment Concierge Service is here to help. Please feel free to contact us at [email protected] to discuss how we can support you.
This position is being recruited on behalf of our client through our Outsourcing service line. Resource Solutions Limited, trading as Robert Walters, acts as an employment business and agency, partnering with top organizations to help them find the best talent. We welcome applications from all candidates and are committed to providing equal opportunities.