Financial Services Risk Management - AML Manager

Responsibilities

As a Manager within the Financial Services Risk Management ("FSRM") Team your role involves developing and implementing risk solutions for financial institutions clients with a focus on Anti-money Laundering ("AML").

• Project delivery and team management:

  • Lead multiple engagements and ensure on-time and high-quality delivery

  • Lead day to day client and stakeholder communication and management

  • Provide coaching and mentoring to junior team members

  • Continuously enhance existing solutions serving for financial crime risk

  • Develop new solutions to address evolving market needs

• Business development/ pitching:

  • Build and maintain relationships with internal and external stakeholders

  • Proactively identify and pursue new opportunities

• Solution development in a wide range of financial service risk management projects in financial crime area, such as:

  • Transaction Monitoring ("TM")

  • Know-your-customer ("KYC")

  • Alert triage

  • Customer risk rating

  • Name screening

  • Fraud detection

• Solution development using advanced technologies including Machine learning ("ML")/ Artificial intelligence ("AI")/ Generative AI ("GenAI") for AML.

Skills

5+ years of work experience with knowledge and hands-on experience in one or more of the following areas:

• AML, Fraud, Sanctions

• Data analytics and ML/AI/GenAI use case development experience in AML

• Experience in developing end-to-end transaction monitoring models/systems, alert triage models, sanctions screening models, and fraud detection models would be a plus

• Possesses strong project management skills and consulting skills, and able to adapt quickly and manage an environment of rapid change and development, and effectively lead others through this process;

• Someone who think out-of-the-box while developing models, reports or data code to solve challenging problems.

Background

• Master’s or bachelor’s degree holder with major in Mathematical, Engineering, Statistical, Quantitative Finance, Computer Science, Data Science, or Artificial Intelligence

• Sound knowledge in statistical, quantitative analysis and data base language, strong background in programming languages (i.e., Python, SAS, R, SQL)

• Experience with deep learning tools such as Keras, TensorFlow, PyTorch, & MXNet

• Experience with natural language processing and large language models

• Proficient in Microsoft Excel, PowerPoint and Word

• Excellent communication and presentation skills, good command of written and spoken Chinese and English

• Ability to work collaboratively with team members and to work independently

• Ability to multi-task, prioritize workload and meet deadlines