You are a strategic thinker passionate about driving solutions using quantitative and Data Science skills. This role will provide the exposure that you need to be successful.

As a Vice President in the Quantitative Insights, Analytics & Advisory (QIAA) team in Wealth Management Solutions, you will oversee the end-to-end lifecycle of AI solutions, from design and development to deployment and continuous testing, ensuring all solutions meet rigorous regulatory and compliance standards.

Job responsibilities

• Develop and articulate the vision, roadmap, and quarterly plans for QIAA’s AI and Data Science team.
• Gain a deep understanding of the Managed Solutions Due Diligence team’s business processes and apply innovative AI and machine learning solutions to drive business enhancement.
• Establish robust testing frameworks and ensure solutions meet appropriate metrics, including implementing continuous automated testing throughout the solution lifecycle.
• Collaborate effectively with business partners, adjacent data science teams, and technology teams to design, develop, and launch impactful solutions.
• Maintain a rigorous controls environment, ensuring all data science solutions comply with relevant governmental procedures and regulatory requirements.

Required qualifications, capabilities, and skills

• 5+ years in quantitative/computational roles and an MS in Data Science or a related ML discipline (e.g., mathematics, statistics).
• Mastery of data science and ML methods, with strong LLM expertise (prompt engineering, context chunking, hyperparameters such as temperature).
• Proficiency in Python and SQL, with a solid understanding of cloud architecture (AWS, Azure) and experience with orchestration and pipelines for ML/AI workloads.
• Proven track record deploying LLM/AI solutions in production at scale, including design, build, testing, and CI/CD—with monitoring, observability, and responsible AI practices in place—especially within regulated environments.
• Excellent communication skills with the ability to translate complex technical concepts for both technical and non-technical audiences.

Preferred qualifications, capabilities, and skills

• Advance degree or equivalent experience in a quantitative, computational, or social science discipline.