Description

About UOB

United Overseas Bank Limited (UOB) is a leading bank in Asia with a global network of more than 500 branches and offices in 19 countries and territories in Asia Pacific, Europe and North America. In Asia, we operate through our head office in Singapore and banking subsidiaries in China, Indonesia, Malaysia and Thailand, as well as branches and offices. Our history spans more than 80 years. Over this time, we have been guided by our values - Honorable, Enterprising, United and Committed. This means we always strive to do what is right, build for the future, work as one team and pursue long-term success. It is how we work, consistently, be it towards the company, our colleagues or our customers.

Job Description

The Investment Products & Solutions division is seeking a Lead Data Scientist to architect and manage the predictive analytics capabilities for our Private Banking unit.

We are currently undertaking a strategic transition from legacy, rule-based advisory logic to a data-driven propensity modeling framework, and to put a data-driven approach at the core of our decision-making process. The objective is to deploy scientifically robust, explainable machine learning models that optimize investment product recommendations for high-net-worth clients and drive our core businesses.

You will report directly to the Head of Digital Advisory (a CFA charterholder). Leveraging my extensive tenure with the bank, I will be deeply engaged in navigating the organizational and business challenges, effectively clearing the path for you to focus on technical architecture and modeling rigor.

Core Responsibilities

• Predictive Modeling: Design and deploy production-grade models using Gradient Boosting frameworks (XGBoost, LightGBM, CatBoost).
• Methodological Rigor: Implement advanced sampling techniques (SMOTE, Class Weights) for imbalanced Private Banking datasets.
• Explainability: Utilize SHAP/LIME to provide transparent rationales for algorithmic recommendations to bankers.
• Financial Feature Engineering: Architect complex feature sets derived from time-series transaction logs.
• Governance: Maintain strict adherence to Model Risk Management (MRM) standards.

Candidate Profile

• Experience: 8-12+ Years. Proven track record in deploying ML models in regulated environments.
• Domain: Deep functional understanding of Wealth Management (Asset Allocation, Rebalancing, Suitability).
• Tech Stack: Python 3.9+, Advanced SQL, Scikit-Learn, XGBoost, SHAP, Airflow, MLflow.

Additional Requirements

Be a Part of the UOB Family

UOB is an equal opportunity employer. UOB does not discriminate on the basis of a candidate's age, race, gender, color, religion, sexual orientation, physical or mental disability, or other non-merit factors. All employment decisions at UOB are based on business needs, job requirements and qualifications. If you require any assistance or accommodations to be made for the recruitment process, please inform us when you submit your online application.

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