Wealth - AI Product Manager - Senior Vice President

Citi•New York, NY

17d

About The Position

Product Strategy & Roadmap: Define and articulate a compelling vision, strategy, and roadmap for the AI product(s), aligning with overall business objectives and technology strategies. Identify new opportunities to leverage AI or to expand the AI product, conducting market research, competitive analysis, customer needs assessments, and understanding business need. Product Development & Lifecycle Management: Lead the end-to-end product lifecycle for AI product(s), from ideation and requirements gathering to development, testing, launch, and post-launch optimization. Work closely with engineering, data science, design, and business teams to ensure successful product delivery. Requirements Definition: Translate complex business problems and user needs into clear, concise, and actionable product requirements and user stories for AI models and platforms. Prioritize features based on business value, technical feasibility, and strategic impact. Stakeholder Management: Collaborate effectively with a diverse set of stakeholders, including senior leadership, business unit heads, technology teams, risk, compliance, and legal, to ensure alignment and secure buy-in for AI product initiatives. AI/ML Expertise: Possess a strong understanding of various AI/ML techniques (e.g., natural language processing, computer vision, predictive analytics, reinforcement learning), their applications, and limitations. Collaborate with technical teams on model selection, data requirements, and solution design. Performance & Metrics: Define key performance indicators (KPIs) and metrics for AI products, monitor performance post-launch and iterate based on data-driven insights. Ensure AI solutions deliver measurable business value. Risk & Compliance: Partner with risk management and compliance teams to ensure all AI products adhere to regulatory requirements, internal policies, and ethical guidelines, particularly concerning data privacy, explainability, and fairness.

Requirements

Bachelor's degree in Computer Science, Engineering, Data Science, Business, or a related field. Master's degree or MBA preferred.
10+ years of experience in product management, with at least 5+ years focused on AI/Machine Learning products.
Proven experience working at an SVP level or equivalent in a large, complex organization, preferably in financial services.
Demonstrated success in defining, launching, and scaling AI products that have delivered significant business impact.
Strong understanding of the financial services industry, including retail banking, institutional clients, wealth management, or enterprise functions.
Solid grasp of AI/ML concepts, algorithms, platforms, and their practical applications.
Familiarity with cloud-based AI/ML services (e.g., AWS Sagemaker, Azure ML, Google AI Platform).
Understanding of data governance, data pipelines, and MLOps principles.
Exceptional communication, presentation, and interpersonal skills, with the ability to articulate complex technical concepts to non-technical stakeholders and senior leadership.
Strong leadership capabilities with the ability to influence, inspire, and drive consensus across diverse teams.
Strategic thinker with a strong analytical and problem-solving mindset.

Responsibilities

Define and articulate a compelling vision, strategy, and roadmap for the AI product(s), aligning with overall business objectives and technology strategies.
Identify new opportunities to leverage AI or to expand the AI product, conducting market research, competitive analysis, customer needs assessments, and understanding business need.
Lead the end-to-end product lifecycle for AI product(s), from ideation and requirements gathering to development, testing, launch, and post-launch optimization.
Work closely with engineering, data science, design, and business teams to ensure successful product delivery.
Translate complex business problems and user needs into clear, concise, and actionable product requirements and user stories for AI models and platforms.
Prioritize features based on business value, technical feasibility, and strategic impact.
Collaborate effectively with a diverse set of stakeholders, including senior leadership, business unit heads, technology teams, risk, compliance, and legal, to ensure alignment and secure buy-in for AI product initiatives.
Possess a strong understanding of various AI/ML techniques (e.g., natural language processing, computer vision, predictive analytics, reinforcement learning), their applications, and limitations.
Collaborate with technical teams on model selection, data requirements, and solution design.
Define key performance indicators (KPIs) and metrics for AI products, monitor performance post-launch and iterate based on data-driven insights.
Ensure AI solutions deliver measurable business value.
Partner with risk management and compliance teams to ensure all AI products adhere to regulatory requirements, internal policies, and ethical guidelines, particularly concerning data privacy, explainability, and fairness.