Responsible for defining data specifications and clarifying logical rules for various types of data (including risk data, financial data, and business data), as well as conducting in-depth data cleansing, feature engineering, and analytical tasks.
Develop data-driven strategic solutions aligned with business objectives and risk appetite to support financial planning and business decision-making.
Automate and optimize existing processes to enhance operational efficiency and accuracy.
Prepare comprehensive model monitoring reports, validation reports, technical presentations, and business requirement specifications to ensure model performance and related strategies comply with regulatory and compliance requirements.
Requirements:
Bachelor's degree or higher in Statistics, Computer Science, Information Systems, Applied Mathematics, or a related quantitative field.
Strong knowledge of Python and SAS, along with foundational and applied understanding of machine learning techniques including Random Forest and XGBoost is desirable.
Prior experience with Large Language Models (LLM) or generative AI applications is a plus.
Strong analytical skills, deep expertise in data analysis, and the ability to exercise sound independent judgment.
Excellent written and spoken English and Chinese; Fluency in Mandarin is advantageous.
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