Data Science & Advanced Analytics

Overview

East West Bank is seeking a highly experienced Data Science & Advanced Analytics leader to spearhead enterprise-scale AI, machine learning, and advanced analytics initiatives that deliver measurable business outcomes across the bank. This role is designed for a hands-on, execution-oriented leader with deep expertise in data-driven decisioning, scalable business analytics, and AI-enabled process transformation within highly regulated industries. The ideal candidate combines strong technical depth with practical business acumen and has a proven track record of building production-grade analytics solutions that improve operational efficiency, revenue growth, customer experience, and risk management.

Responsibilities

• Lead the design, development, and deployment of enterprise AI, machine learning, and advanced analytics solutions across key banking domains including risk, fraud, AML/BSA, customer analytics, cross-selling, and operational intelligence.
• Drive end-to-end analytics delivery from business problem definition through data engineering, feature engineering, model development, deployment, monitoring, and business adoption.
• Build scalable and production-grade data science and machine learning capabilities leveraging Azure-native and distributed computing frameworks including Azure ML, Databricks, Spark, and cloud-based data platforms.
• Operationalize developed solutions within core business processes and decision workflows to drive measurable business value and adoption.
• Partner with engineering teams to integrate models into enterprise systems through APIs, microservices, and modern data platforms.
• Drive model governance, explainability, monitoring, validation, recalibration, and regulatory compliance activities aligned with banking and model risk expectations.
• Establish best practices for tech stack choices, MLOps, model lifecycle management, CI/CD automation, experiment tracking, and production monitoring.
• Collaborate cross-functionally with business, risk, compliance, legal, audit, and technology stakeholders to ensure responsible and scalable AI adoption.
• Mentor and lead high-performing analytics and data science teams, including distributed or offshore resources where applicable.
• Translate complex analytical insights into executive-level recommendations and measurable business outcomes.

Qualifications

• 10+ years of hands-on experience in data science, advanced analytics, AI/ML engineering, or quantitative modeling, including leadership experience within financial services, fintech, insurance, or other regulated industries.
• Proven track record delivering production-grade AI and analytics solutions with measurable business impact in complex enterprise environments.
• Deep hands-on expertise in Python, SQL, machine learning frameworks, statistical modeling, predictive analytics, and distributed data processing.
• Strong practical experience with modern AI/ML tooling and platforms including Azure ML, Databricks, Spark, TensorFlow, PyTorch, scikit-learn, XGBoost, MLflow, and cloud-native analytics ecosystems.
• Experience implementing scalable MLOps frameworks including model deployment, CI/CD automation, model monitoring, experiment tracking, and governance controls.
• Strong understanding of model risk management, explainability, auditability, data governance, privacy, and regulatory expectations within regulated industries.
• Hands-on experience integrating analytics and AI solutions into enterprise applications, APIs, operational workflows, and decision systems.
• Strong process orientation with the ability to redesign workflows and operational models using data-driven insights and AI-enabled automation.
• Demonstrated ability to influence senior executives and drive cross-functional execution across business, technology, risk, and operations teams.
• Excellent communication, stakeholder management, and executive presentation skills.
• Bachelor’s degree in Data Science, Computer Science, Statistics, Mathematics, Engineering, or related quantitative discipline.

Highly Preferred

• Direct experience building AI and analytics capabilities within commercial banking, consumer banking, payments, lending, fraud, AML/BSA, or regulatory reporting environments.
• Experience deploying Generative AI, LLM, NLP, or intelligent automation use cases (Lead Generation, Next Best Action, Banker copilot, etc.) in production environments.
• Strong knowledge of SR 11-7, CCAR, CECL, BCBS 239, and enterprise governance frameworks related to AI and model risk.
• Experience designing enterprise feature stores, vector-based retrieval systems, or real-time inference architecture.
• Experience leading enterprise AI transformation initiatives from proof of concept through scaled production adoption.
• Master’s degree or PhD in quantitative discipline.
• Demonstrated ability to build, retain, and scale high-performing analytics organizations.
• Applicants must have legal authorization to work in the United States. We do not offer visa sponsorship at this time.

Pay

The base pay range for this position is USD $175,000.00/Yr. - USD $275,000.00/Yr. Exact offers will be determined based on job-related knowledge, skills, experience, and location.