Fraud Threat and Forensics Expert

As a Fraud Threat and Forensics Analyst/Expert within the Middle-Office department, you will play a critical role in identifying, analyzing, and mitigating financial crime threats through advanced forensic investigations and data-driven insights. Leveraging your expertise in digital forensics, threat intelligence, and data analysis, you will develop, enhance, and maintain cutting-edge Fraud and Anti-Money Laundering (AML) detection solutions. This role involves collaborating with cross-functional teams to design and implement robust detection frameworks, proactively addressing emerging risks, and ensuring the reliability and effectiveness of analytical tools. By staying ahead of evolving technologies and threat landscapes, you will contribute to strategic decision-making and drive innovation in financial crime prevention.

Threat and forensics management

• Demonstrate the ability to maintain a comprehensive 360-degree view of customer profiles and behaviors by integrating and correlating diverse data sources, such as digital traffic, payment patterns, personal details, and external intelligence, to identify anomalies, detect fraudulent activities, and strengthen financial crime prevention measures.
• Lead the detailed analysis and definition of data requirements within the fraud and financial crime threat intelligence lifecycle, focusing on transforming raw data into actionable insights to optimize detection frameworks, improve risk assessment accuracy, and facilitate the development of targeted mitigation strategies.
• Drive the development and continuous improvement of advanced Fraud and AML detection and prevention solutions.
• Collaborate with IT, software engineering, and data teams to identify, map, and integrate new data sources for enhanced threat detection and forensics capabilities.
• Develop and fine-tune detection rules and models to support proactive threat hunting, anomaly detection, and financial crime mitigation.
• Contribute to the design, implementation, optimization and execution of operational and administrative controls to strengthen fraud defenses.
• Facilitate the automation of fraud processes to reduce manual workloads and improve efficiency across workflows.
• Create and maintain detailed documentation for detection tools, data flows, and related systems to ensure transparency and consistency.
• Design and track performance metrics for detection systems, continuously refining KPIs and KRIs to measure effectiveness.
• Leverage a systematic and analytical approach to problem-solving, demonstrate strong communication and collaboration skills, and take ownership of responsibilities to drive results.

Risk management

• Assist the team in conducting comprehensive fraud and risk assessments for new business initiatives and support business teams in implementing effective mitigation strategies.
• Ensure that all identified product and customer risks are effectively mapped and mitigated through the detection use case library and the capabilities of the Fraud & AML platform.
• Conduct threat modeling to identify potential vulnerabilities, assess risks, and design effective countermeasures to strengthen the organization's fraud defenses.
• Provide assistance and support to clients and partners on fraud-related issues and inquiries.

Fraud incident Management

• Lead the incident response process, including conducting detailed forensic analyses of fraud incidents, documenting evidence comprehensively, and ensuring proper reporting and follow-up actions.
• Collaborate closely with IT and Operations teams to ensure swift and effective resolution of fraud incidents.
• Actively engage in team responsibilities and related activities, contributing to the overall success of the Fraud function.

Mandatory

• Bachelor’s or Master’s degree in Data Science, Computer Science, Forensic Accounting, or a related field.
• Extensive experience in reporting and data analytics, with over 5 years of expertise in data visualization, querying, and interpreting complex datasets to inform and support strategic business decision-making.
• Deep understanding of AML and fraud prevention frameworks, with proven hands-on experience in threat modelling, e-discovery and digital forensics (mandatory).
• Experience with threat intelligence lifecycle, including collection, analysis, and dissemination of actionable intelligence to identify and mitigate financial crime threats effectively.
• Proficiency in data analysis and visualization tools, including but not limited to Snowflake, Tableau, Elastic Stack or similar.
• Advanced knowledge of data mining, visualization, and machine learning applications for fraud detection and risk mitigation.
• Experience working with both relational and non-relational databases, with the ability to write and execute queries (e.g., ES|QL, SQL), as well as proficiency in scripting languages such as Python, Perl, or Bash (being able to extract the data, manipulate it, write the logic etc.).
• Excellent oral and written communication skills, with the ability to effectively interact with diverse stakeholders, subject matter experts, and third-party vendors, including vendor management.
• Ability to distill and communicate complex technical concepts in clear and actionable business language.
• Proficiency in English is mandatory.

Preferred

• Experience in roles such as Product Owner or Project Manager, with a proven track record of successfully delivering projects of varying scope and complexity.
• Proven ability to apply both expert-driven rules and machine learning techniques to detect fraud.
• Hands-on experience in the automation of financial crime processes to enhance efficiency.
• Expertise in internal fraud investigations, including prevention and mitigation strategies.
• Strong awareness of market trends with the ability to anticipate and address evolving end-user expectations and demands.

• Technical and business knowledge of AML/CTF and fraud regulations is an advantage (FINMA, PSD, MAS, HKM etc.).

• Proficiency in French.

Bonus for

• Certifications in AML or fraud prevention e.g. CAMS, CFE, CISA
• Information Security certificates e.g. CISSP/CISA/GIAC/CEH
• Data Science trainings/certifications

SQ2