Private Bank - Lead Data Scientist

UOB • Phoenix, AZ

58d

About The Position

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.

Requirements

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

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.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: No Education Listed
• Number of Employees: 5,001-10,000 employees