The Senior Data Scientist is responsible for delivering AI-driven intelligence, advanced analytics, and decision-support capabilities that improve advisor productivity, client engagement, operational efficiency, and regional business growth across Wealth Management. This role partners closely with regional business leadership, advisors, Data & AI teams, and Technology partners to identify high-value opportunities and rapidly deliver practical AI and analytical solutions aligned to regional priorities. What will you do? Lead development of AI and analytical capabilities aligned to regional Wealth Management priorities including advisor productivity enhancement, client engagement intelligence, household insights, pipeline analytics, and attrition indicators. Partner directly with regional business leadership and advisor teams to identify high-impact AI opportunities, prioritize use cases, and translate business challenges into analytical solutions. Design and embed decision intelligence capabilities directly into advisor and operational workflows, including advisor copilots, meeting preparation intelligence, and opportunity scoring. Develop and operationalize advanced analytics models including predictive models, recommendation systems, segmentation models, and NLP/ Gen. AI-powered solutions end-to-end. Support regional AI incubation through rapid prototyping, hypothesis testing, and iterative learning with controlled experimentation and modular solution design. Present analytical findings and AI recommendations to leadership audiences and drive adoption of AI-enabled workflows. Collaborate with Data Engineering and AI Engineering teams on deployment, operationalization, and continuous monitoring of analytical solutions. Ensure all solutions align with Model Risk Management standards, data governance, privacy policies, responsible AI principles, and enterprise architecture requirements. What do you need to succeed? Must-have 5 years of experience as a Data Scientist or Analytics professional delivering machine learning and AI solutions in business environments. Strong proficiency in Python/ SQL, predictive modeling, statistical analysis, and cloud-based analytics environments. Demonstrated ability to translate complex business problems into analytical and AI requirements with measurable success metrics. Deep understanding of Wealth Management business models, advisor workflows, and client engagement strategies. Strong executive communication skills with ability to simplify complex concepts and influence across business and technology teams. Nice-to-have. Experience with Generative AI, NLP, ML - Ops concepts, and model lifecycle management. Background in financial services and familiarity with financial products, portfolio concepts, and household analytics. What’s in it for you?