Fraud & AML Analytics Manager

WorldFirst; London; On-site; GBP 40,000 - 80,000; Full time

Job summary

An established industry player is seeking a skilled data analyst to govern anti-money laundering and compliance data. This role involves driving risk management, supporting compliance teams, and innovating with technical teams to enhance automation. Candidates should have a strong background in data analysis and project management, with proficiency in SQL and analytical tools like SAS or Python. Join a dynamic team where your contributions will directly impact compliance strategies and data integrity in a fast-paced environment. If you thrive under pressure and are passionate about data-driven solutions, this opportunity is for you.

Qualifications

• 2+ years of experience in big data risk control analysis and modeling.
• Proficient in SQL and skilled in using analysis tools like SAS or Python.

Responsibilities

• Governance of anti-money laundering and compliance data for accuracy.
• Drive identification and management of compliance risks using data-driven methods.

Skills

SQL

Data Analysis

Project Management

Team Collaboration

Communication Skills

Education

Bachelor’s degree in Statistics

Bachelor’s degree in Mathematics

Bachelor’s degree in Computer Science

Tools

SAS

Python

R

Job description

Main responsibilities include:

1. Responsible for the governance of underlying anti-money laundering/sanctions/global trade compliance data to ensure the accuracy and completeness of data used by strategies, models, and systems.
2. Drive the identification and management of anti-money laundering/sanctions/global trade compliance risks using data-driven methods, assisting compliance officers in formulating effective risk control plans.
3. Support site compliance teams in responding to regular or ad-hoc internal and external regulatory inspections, providing regulatory reporting and data support.
4. Innovate with technical and algorithm teams to enhance automation in quantitative strategy qualification and improve manual review efficiency through big model-driven methods.

Requirement：

1. Bachelor’s degree or above in relevant fields such as statistics, mathematics, computer science, etc.2. At least two years of experience in big data risk control analysis and modeling, preferably in industries such as banking, third-party payment institutions, or fintech, with a preference for anti-money laundering/sanctions/global trade compliance experience.3. Proficient in SQL data processing and skilled in using at least one professional analysis tool, such as SAS, Python, R, etc.4. Strong project management experience, good team collaboration skills, and ability to work under pressure.5. Fluent in English listening, speaking, reading, and writing; proficiency in Chinese communication is preferred.