Fraud Data Analyst

Marcura; London; On-site; GBP 40,000 - 60,000; Full time

Job summary

A leading company in the banking industry is seeking a Fraud Data Analyst in London to enhance their fraud prevention strategies. You will work closely with the Compliance team to mitigate fraudulent activities using your expertise in data analysis, Python, and SQL. This role involves analyzing transaction patterns, developing predictive models, and ensuring adherence to regulatory standards, making it suitable for candidates with a strong analytical background and relevant experience.

Benefits

Competitive Salary and Bonus

Inclusive Onboarding Experience

Marcura Wellness Zone

Global Opportunities

Diverse, Supportive Work Culture

Qualifications

• 3-5 years of experience in fraud prevention and data analysis within Fintech or Banking.
• Ability to write complex SQL queries and use Python for data analysis.
• Familiarity with machine learning and statistical analysis.

Responsibilities

• Analyze transaction data to identify patterns indicative of fraudulent activities.
• Develop and implement data-driven fraud detection rules and models.
• Ensure compliance with UK regulations including GDPR and PCI DSS.

Skills

Analytical mindset

Fraud detection expertise

Data analysis

Problem-solving

Communication

Education

Professional certifications in fraud detection or data analytics

Tools

SQL

Python

Data Visualization Tools

Machine Learning

Job description

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

Base pay range

As a Fraud Data Analyst, you will play a critical role in detecting, analysing, and mitigating fraudulent activities across card and wire transactions. You will work closely with the Transaction Monitoring Manager and the broader Compliance team to ensure the integrity and security of our payment systems. Your role will involve leveraging data analytical skills, Python, SQL, and various analytical tools to identify suspicious activities, enhance fraud detection strategies, and support decision-making processes.

Your new day-to-day will involve:

• Fraud Detection and Analysis:

o Analyse transaction data to identify patterns and trends indicative of fraudulent activities.

o Investigate and monitor real-time transaction alerts to detect potential card fraud.

o Develop and implement data-driven fraud detection rules and models.

o Analyse false positives to refine and optimize fraud detection systems.

o Ensure that the company's financial practices comply with statutory regulations and legislation.

• Data Management and Analysis:

o Extract, clean, and manage large datasets using SQL and Python for in-depth analysis.

o Utilize data analytics tools to track, analyse, and report on key fraud metrics and KPIs.

o Create dashboards and reports that communicate actionable insights to stakeholders.

o Collaborate with IT and Data teams to improve data quality and accessibility.

o Build and maintain predictive models using machine learning algorithms to identify fraudulent activities.

o Test, evaluate, and fine-tune models to improve fraud detection accuracy and reduce false positives.

o Document methodologies and results, ensuring they are well understood by both technical and non-technical stakeholders.

• Collaboration with Cross-Functional Teams:

o Work closely with the Product, Operations, Risk, and Compliance teams to respond quickly to emerging threats.

o Support the Transactions Monitoring Manager and Compliance Operations Manager in strategic fraud prevention initiatives and projects.

o Liaise with external partners, including banks, card issuers and processors, payment processors to gather intelligence on evolving fraud trends.

• Regulatory and Compliance Adherence:

o Ensure compliance with UK regulations, including GDPR, PCI DSS, and industry best practices related to card fraud prevention.

o Keep up to date with relevant legislation, ensuring that fraud detection activities are aligned with legal requirements.

o Monitor the effectiveness of existing fraud detection measures and recommend improvements.

o Stay informed about the latest trends in fraud detection and payment technology.

o Participate in fraud prevention workshops, conferences, and training sessions to enhance skill sets.

As a Fraud Data Analyst, you will play a critical role in detecting, analysing, and mitigating fraudulent activities across card and wire transactions. You will work closely with the Transaction Monitoring Manager and the broader Compliance team to ensure the integrity and security of our payment systems. Your role will involve leveraging data analytical skills, Python, SQL, and various analytical tools to identify suspicious activities, enhance fraud detection strategies, and support decision-making processes.

Your new day-to-day will involve:

• Fraud Detection and Analysis:

o Analyse transaction data to identify patterns and trends indicative of fraudulent activities.

o Investigate and monitor real-time transaction alerts to detect potential card fraud.

o Develop and implement data-driven fraud detection rules and models.

o Analyse false positives to refine and optimize fraud detection systems.

o Ensure that the company's financial practices comply with statutory regulations and legislation.

• Data Management and Analysis:

o Extract, clean, and manage large datasets using SQL and Python for in-depth analysis.

o Utilize data analytics tools to track, analyse, and report on key fraud metrics and KPIs.

o Create dashboards and reports that communicate actionable insights to stakeholders.

o Collaborate with IT and Data teams to improve data quality and accessibility.

• Model Development:

o Build and maintain predictive models using machine learning algorithms to identify fraudulent activities.

o Test, evaluate, and fine-tune models to improve fraud detection accuracy and reduce false positives.

o Document methodologies and results, ensuring they are well understood by both technical and non-technical stakeholders.

• Collaboration with Cross-Functional Teams:

o Work closely with the Product, Operations, Risk, and Compliance teams to respond quickly to emerging threats.

o Support the Transactions Monitoring Manager and Compliance Operations Manager in strategic fraud prevention initiatives and projects.

o Liaise with external partners, including banks, card issuers and processors, payment processors to gather intelligence on evolving fraud trends.

• Regulatory and Compliance Adherence:

o Ensure compliance with UK regulations, including GDPR, PCI DSS, and industry best practices related to card fraud prevention.

o Keep up to date with relevant legislation, ensuring that fraud detection activities are aligned with legal requirements.

• Continuous Improvement:

o Monitor the effectiveness of existing fraud detection measures and recommend improvements.

o Stay informed about the latest trends in fraud detection and payment technology.

o 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:

o Advanced SQL: Ability to write complex queries for extracting and analysing large datasets.

o Python: Proficient in using Python for data analysis, automation, and model development.

o Data Visualization Tools: Experience with tools like Metabase, Tableau, Power BI, or similar for creating insightful dashboards.

o Machine Learning: Familiarity with machine learning concepts and their application in fraud detection.

o Statistical Analysis: Strong foundation in statistics, including experience with hypothesis testing, regression analysis, and probability theory.

• Fraud and Risk Management Expertise:

o In-depth understanding of card fraud typologies and techniques, including phishing, card-not-present (CNP) fraud, and card-present fraud.

o Experience in building and analysing fraud detection rules, thresholds, and scoring systems.

o Awareness of financial industry standards and best practices for fraud detection.

• Analytical Mindset:

o Strong problem-solving skills with a keen eye for detail.

o Ability to interpret complex data and turn it into actionable insights.

o Familiarity with anomaly detection and pattern recognition techniques.

• Communication and Stakeholder Management:

o Excellent communication skills with the ability to translate complex data findings into clear insights for non-technical stakeholders.

o Experience working within cross-functional teams, effectively managing relationships with internal and external partners.

o Strong report writing and presentation skills.

Benefits

• Competitive Salary and Bonus: We reward your expertise and contributions.
• Inclusive Onboarding Experience: Our onboarding program is designed to set you up for success right from day one.
• Marcura Wellness Zone: We value your work-life balance and well-being.
• Global Opportunities: Be part of an ambitious, expanding company with a local touch.
• Diverse, Supportive Work Culture: We're committed to inclusion, diversity, and a sense of belonging for all team members.

Seniority level

• Seniority level

  Associate

Employment type

• Employment type

  Full-time

Job function

• Job function

  Legal

• Industries

  Banking

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