Fraud Data Analyst

3 weeks ago

London, United Kingdom MarTrust Full time
About the Role

We are seeking a highly skilled Fraud Data Analyst to join our team at MarTrust, a leading provider of digital payment solutions in the shipping industry. As a Fraud Data Analyst, you will play a critical role in detecting, analyzing, and mitigating fraudulent activities across card and wire transactions.

Key Responsibilities
  • Fraud Detection and Analysis
    • Analyze transaction data to identify patterns and trends indicative of fraudulent activities.
    • Investigate and monitor real-time transaction alerts to detect potential card fraud.
    • Develop and implement data-driven fraud detection rules and models.
    • Analyze false positives to refine and optimize fraud detection systems.
    • Ensure that the company's financial practices comply with statutory regulations and legislation.
  • Data Management and Analysis
    • Extract, clean, and manage large datasets using SQL and Python for in-depth analysis.
    • Utilize data analytics tools to track, analyze, and report on key fraud metrics and KPIs.
    • Create dashboards and reports that communicate actionable insights to stakeholders.
    • Collaborate with IT and Data teams to improve data quality and accessibility.
  • Model Development
    • Build and maintain predictive models using machine learning algorithms to identify fraudulent activities.
    • Test, evaluate, and fine-tune models to improve fraud detection accuracy and reduce false positives.
    • Document methodologies and results, ensuring they are well understood by both technical and non-technical stakeholders.
  • Collaboration with Cross-Functional Teams
    • Work closely with the Product, Operations, Risk, and Compliance teams to respond quickly to emerging threats.
    • Support the Transactions Monitoring Manager and Compliance Operations Manager in strategic fraud prevention initiatives and projects.
    • Liaise with external partners, including banks, card issuers and processors, payment processors to gather intelligence on evolving fraud trends.
  • Regulatory and Compliance Adherence
    • Ensure compliance with UK regulations, including GDPR, PCI DSS, and industry best practices related to card fraud prevention.
    • Keep up to date with relevant legislation, ensuring that fraud detection activities are aligned with legal requirements.
  • Continuous Improvement
    • Monitor the effectiveness of existing fraud detection measures and recommend improvements.
    • Stay informed about the latest trends in fraud detection and payment technology.
    • Participate in fraud prevention workshops, conferences, and training sessions to enhance skill sets.
Requirements
  • Professional certifications in fraud detection, data analytics, or related fields are a plus.
  • Minimum of 3-5 years of experience in a similar role, with a focus on fraud prevention and data analysis within Fintech or Banking.
  • Technical Skills:
    • Advanced SQL: Ability to write complex queries for extracting and analyzing large datasets.
    • Python: Proficient in using Python for data analysis, automation, and model development.
    • Data Visualization Tools: Experience with tools like Metabase, Tableau, Power BI, or similar for creating insightful dashboards.
    • Machine Learning: Familiarity with machine learning concepts and their application in fraud detection.
    • Statistical Analysis: Strong foundation in statistics, including experience with hypothesis testing, regression analysis, and probability theory.
  • Fraud and Risk Management Expertise:
    • In-depth understanding of card fraud typologies and techniques, including phishing, card-not-present (CNP) fraud, and card-present fraud.
    • Experience in building and analyzing fraud detection rules, thresholds, and scoring systems.
    • Awareness of financial industry standards and best practices for fraud detection.
  • Analytical Mindset:
    • Strong problem-solving skills with a keen eye for detail.
    • Ability to interpret complex data and turn it into actionable insights.
    • Familiarity with anomaly detection and pattern recognition techniques.
  • Communication and Stakeholder Management:
    • Excellent communication skills with the ability to translate complex data findings into clear insights for non-technical stakeholders.
    • Experience working within cross-functional teams, effectively managing relationships with internal and external partners.
    • Strong report writing and presentation skills.

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