Senior Data Analyst – Fraud Strategy
We are looking for an experienced fraud strategy professional who is highly data literate with a strong understanding of fraud typologies, detection data, and trade‑offs between fraud prevention and sales, to join our Financial Services team.
Responsibilities
* Provide support in all aspects of consumer fraud and financial crime, including knowledge of first‑ and third‑party fraud typologies and fraud detection data, techniques and platforms.
* Oversee the fraud control rule structure, working closely with third‑party fraud prevention solution providers (e.g. LexisNexis ThreatMetrix), and lead continuous improvement in fraud strategy.
* Own, design and implement fraud strategies to detect and prevent third‑party consumer credit fraud such as impersonation and account takeover, and first‑party fraud (e.g. from customer claims), including UAT within our fraud decision systems.
* Use data analysis and modelling techniques to conduct complex analysis, continually optimise rules to detect fraud whilst minimising impact on good sales, and present findings and recommendations to the Leadership Team.
* Evolve fraud strategy monitoring, with written evaluation of performance, highlighting emerging risks or trends and initiating further actions and analysis.
* Monitor KPIs and KRIs to ensure new fraud risks and emerging trends are detected and reviewed in a timely fashion, and strategy changes are working as expected.
* Lead fraud business initiatives, providing SME input to delivery leads.
* Build effective collaborations with other business areas and product owners across the company to ensure business change initiatives are delivered in line with fraud risk appetite and appropriate fraud controls.
* Develop key stakeholder relationships both internally and externally.
* Maintain knowledge of regulatory changes, ensuring fraud strategies adhere to all governance, financial crime and compliance standards.
* Support the delivery of fraud and financial crime capabilities and strategies into the new Financial Services platform.
Qualifications
* Degree in a STEM subject.
* Previous experience in data analysis and strategy development for fraud prevention and detection, working for a direct‑to‑consumer lender.
* Highly analytical with a demonstrated ability to solve problems through logical thinking.
* Experience using SQL, SAS or Python for data mining and analysis.
* Comfortable extracting and analysing large datasets using SQL.
* Excellent presentation skills and ability to explain complex analysis simply and concisely using Microsoft Office.
* Excellent organisational skills to prioritise and deliver required output accurately and in a timely fashion.
* Strong collaboration skills, building relationships with peers across the business (e.g. operational departments and digital technology).
* High attention to detail and routinely incorporate checks to ensure accuracy.
* Self‑starter who takes initiative and can work with ambiguity.
Desirable
* Experience in a consumer fraud analytical role for an online retail lender.
* Experience working with fraud decision systems (e.g. CyberSource, ThreatMetrix, Mitek).
* Experience with fraud models and understanding of model performance measurement and drift.
* Experience in fraud model development.
Benefits
* Hybrid working (2–3 days in the office at a minimum).
* 24 days holiday (+ 8 bank holidays).
* Annual bonus scheme.
* Enhanced maternity and adoption leave.
* Company pension with up to 8% N Brown contribution.
* Mental health support, including wellbeing champions and counselling services.
* Financial wellbeing support, including the Stream tool to track pay, access earnings early and manage money.
* Colleague discounts across all N Brown brands.
* Onsite café with subsidised rates and local restaurant discounts.
* Life assurance and private medical insurance.
* Paid volunteer time – a full day paid to volunteer for a chosen charity.
Equal Opportunity Employer
We are an equal opportunity employer and value diversity. We do not discriminate based on race, religion, colour, national origin, sex, gender, gender expression, sexual orientation, age, marital status, veteran status or disability status.
J-18808-Ljbffr