Full-Stack Product Manager - Global Risk

Full-Stack Product Manager

Risk & Analytics Products (RAP) is a full-stack product team focusing on developing platforms for Risk and analytical applications. We use mathematical modeling and the latest technologies to build loss forecasting, stress testing pipelines, and other Risk applications for the firm. Our systems are responsible for calculating risk on some of the largest portfolios in Citi.

We are a diverse group of professionals with backgrounds in Physics, Engineering and Computer Science, Design, and Liberal Arts. You will work alongside experienced colleagues to further develop your analytical, quantitative, and technical skills. You will build skills in building products end-to-end from the ground up to solve real life problems and develop a career as a full-stack product expert.

Key Responsibilities:

• Engage and interview clients for user research and establish user stories through product discovery process to define product strategy and roadmap
• Develop a deep understanding of clients’ needs, both from a business and data perspective, and translate them into product features as their advocate
• Own and deliver the product roadmap from developing wireframes to testing and rolling-out new features
• Track the progress of the team’s delivery cycles, prioritize features, and manage backlogs through an agile process
• Collaborate with designers, developers, and quants and provide insights to align each process to the overall product vision
• Become a subject matter expert in your area to provide a positive onboarding experience for the clients and resolve any post-rollout issues
• Design, implement, and track success metrics for product outcomes

Qualifications:

• Bachelors or Masters in a quantitative discipline like financial engineering, economics, mathematics, statistics, etc., or equivalent experience
• Experience working as a Product Manager, Product Owner, or other Product-focused roles
• Basic proficiency in Python, SQL and Linux.
• Strong grasp in product management fundamentals
• Strong grasp in LLMs, Prompt Engineering, and Agentic workflows
• Familiarity in data analysis and quantitative methods such as regression, machine learning, EDA.
• Problem solving skills to deconstruct problems with a data driven approach
• Interest in developing a career in finance, especially in the field of Risk Management.