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Financial Services Risk Management

Background

Within EY FSO Advisory Practice, the Financial Services Risk Management (FSRM) group provides solutions that can help FSO clients identify, measure, manage and monitor AI risk and anti-money laundering.

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

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