Model Risk Data Scientist for Financial Crime Prevention

Key Skills

C Programming, C++, Cloud computing, Data science techniques, Java Programming, Machine learning techniques, MATLAB Programming, Python Programming, PyTorch, R Programming, Scala Programming, SQL, TensorFlow

Job Description

Do you want to apply advanced data science and programming skills to keep criminals from abusing the financial systems? Are you an innovative thinker? We’re looking for a Model Risk Data Scientist who can:

• independently review models for Financial Crime Prevention models and Anti-Money Laundry (AML) models used in Investment Bank and Wealth Management
• assess the conceptual soundness and appropriateness of different models and perform related outcome, impact and benchmark analyses
• design and perform validation tests to assess the correctness and stability of the implementation
• carry out and document independent model validation in line with regulatory requirements and internal standards
• interact and discuss with model users, developers, senior owners of Financial Crime Prevention business representatives and governance bodies

Your team

You’ll be working in the APAC team of the Model Risk Management and Control (MRMC) based in Shanghai. The main objective of the team is to work closely with MRMC teams from other locations like Zurich and London to validate the models used in Investment Bank and China entities.

Your expertise

You have:

• BSc or MSc/PhD in a computational discipline such as Computer Science, Data Analytics, Data Science, Engineering, Mathematics, Statistics, Physics, Economics etc
• Extensive experience in Financial Crime Prevention models and Anti-Money Laundry (AML) models is required for Director role
• fresh graduates are welcomed to apply for junior role
• proficiency using Python/SQL/R/C++ or other computer language in scientific or numerical computation
• added advantage for experience in AI, Machine Learning or AML models
• good written and verbal communication skills

You are:

• independent, pragmatic, concise and accurate, with strong attention to detail
• able to apply technical understanding to practical problems
• willing to collaborate and share knowledge with your team