Fraud Data Analyst

Consortia; London; On-site; GBP 45,000 - 65,000; Full time

Job summary

A leading company based in London is seeking an experienced Fraud Data Analyst to mitigate fraud risks and enhance financial integrity. The successful candidate will utilize advanced data techniques, collaborate with various teams, and ensure compliance with UK regulations, making a measurable impact on fraud prevention strategies.

Qualifications

• 3–5 years of experience in a Fraud Data Analyst or similar role within payments, fintech, or banking.
• Expertise in fraud typologies including phishing and payment fraud.
• Ability to analyse anomalies and identify trends.

Responsibilities

• Monitor card and wire transactions to detect patterns associated with fraudulent behaviour.
• Extract and analyse large volumes of transactional data using SQL and Python.
• Maintain compliance with UK regulatory standards, including GDPR and PCI DSS.

Skills

SQL

Python

Data visualisation tools

Statistical methods

Machine learning

Communication

Education

Bachelor's degree in relevant field

Job description

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This range is provided by Consortia. Your actual pay will be based on your skills and experience — talk with your recruiter to learn more.

Base pay range

Direct message the job poster from Consortia

AD @ Consortia | Scaling AI and Engineering teams with elite technical talent | The Recruitment GOAT

We are seeking an experienced Fraud Data Analyst to support the detection, analysis, and prevention of fraud across card and wire payment channels. This role plays a vital part in a dynamic compliance and risk function, using advanced data techniques to help protect customers and the integrity of payment systems.

You will work across teams to investigate suspicious activity, develop fraud models, and optimise transaction monitoring strategies using Python, SQL, and modern analytics tools.

Key Responsibilities

Fraud Detection and Investigation

• Monitor card and wire transactions to detect patterns associated with fraudulent behaviour
• Respond to real-time alerts and proactively identify potential fraud threats
• Develop and refine fraud rules and detection models to improve efficiency
• Conduct root-cause analysis of false positives to fine-tune detection strategies
• Ensure all fraud-related processes remain compliant with current financial regulations

Data Analysis and Reporting

• Extract and analyse large volumes of transactional data using SQL and Python
• Build and maintain dashboards and reports that highlight fraud trends and KPIs
• Improve access to fraud data through collaboration with engineering and data teams
• Present complex data findings to stakeholders in a clear and actionable manner
• Create predictive models and apply machine learning techniques to identify fraud risks
• Continuously evaluate and enhance fraud models to maintain detection accuracy
• Maintain clear documentation of methodology for use across both technical and non-technical audiences
• Work closely with product, operations, compliance, and risk teams to align on fraud mitigation approaches
• Support strategic fraud initiatives and investigations led by the Transactions Monitoring and Compliance functions
• Liaise with third parties such as card issuers, processors, and financial institutions to share insights and trends

Regulatory Awareness and Continuous Improvement

• Maintain compliance with UK regulatory standards, including GDPR and PCI DSS
• Monitor the performance of fraud controls and identify areas for enhancement
• Keep up to date with emerging fraud techniques and innovations in detection
• Attend relevant training, workshops, or forums to enhance your expertise as a Fraud Data Analyst

Requirements

• 3–5 years of experience in a Fraud Data Analyst or similar role within payments, fintech, or banking
• Expertise in fraud typologies including phishing, CNP fraud, and payment fraud
• Strong skills in:
• SQL – complex queries and data extraction
• Python – for analysis, automation, and model development
• Data visualisation tools such as Power BI, Metabase, or Tableau
• Statistical methods, including regression and hypothesis testing
• Basic understanding of machine learning as applied to fraud detection
• Ability to analyse anomalies, identify trends, and convert findings into prevention strategies
• Excellent communication and stakeholder engagement skills
• A strong attention to detail and ability to work collaboratively across departments

This is an exciting opportunity for a Fraud Data Analyst to have a measurable impact in reducing risk and supporting financial integrity. If you are a data-driven professional with a passion for fraud prevention, we want to hear from you.

Apply now to join a team where your skills as a Fraud Data Analyst can truly make a difference.

Seniority level

• Seniority level

  Mid-Senior level

Employment type

• Employment type

  Full-time

Job function

• Job function

  Information Technology, Analyst, and Product Management

• Industries

  Financial Services, Banking, and Software Development

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