Job Overview: IT - Data Analyst - Intermediate

The team requires 12 months of support to manage BAU activities such as incident analytics while expanding engagements with other teams. The role involves threat detection, use case development, and automation. The ideal candidate is not a data scientist, but a data analyst with strong technical skills (Python, SQL) and a background in fraud, AML, corporate security, and cyber investigations. An investigator mindset is highly valued.

JOB DESCRIPTION

Reporting to the Director of Fusion Data & Analytics, the Analytics Consultant will collaborate closely with various partners across Lines of Business (LOBs) to analyze data that supports effective incident response and to develop threat detection logic utilizing cross-pillar datasets. The Fusion Data & Analytics team is committed to leveraging data & analytics to safeguard Company's clients, employees, and assets from financial crimes. In this role, you will conduct data analysis to uncover emerging behaviors and patterns of threat actors concealed within the data.

How you’ll succeed

• Analytics support for incident response – Enable swift incident response by supporting any data and analysis needs during incidents. Work closely with Fusion Response team and various business owners to deliver the required data to respond to incidents effectively.
• Threat detection logic development – Use cross-domain data to develop detection logics for various threat scenarios. Work closely with business partners to understand the detection targets and their behaviours to come up with alerts that will mitigate the risk.
• Automation - Support Fusion continuous improvement initiative with automation. Use your programming skills to enable business partners and innovate existing manual processes.
• Documentation – Document data models, threat detection logic and business background of use cases, and various other day to day task.

Must-Have Skills:

• Strong technical analytics skills (SQL, Python)
• Experience with PySpark (ideal but not mandatory)
• Solid understanding of Corporate Security, AML, Fraud, and Cybersecurity
• Background in fraud investigation or similar roles, with an investigator mindset
• Business acumen combined with technical skills (data analyst with investigative and threat detection experience)
• Familiarity with threat detection, incident analytics, and use case development
• Excellent communication skills and ability to take initiative

Nice-to-Have:

• Experience with documentation and administrative tasks to support technical work organization