Trading Book Data and Analytics

Sumitomo Mitsui Banking Corporation•New York, NY

8d•$152,000 - $195,000•Hybrid

About The Position

SMBC is seeking a Vice President (VP) for the Trading Book Risk Modeling team within the Risk Modeling Center of Excellence (COE). This role will be instrumental in advancing the firm's data analytics and AI capabilities to support trading book risk modeling. The successful candidate will combine expertise in quantitative analytics, market risk methodologies, and emerging AI technologies to develop innovative, production-grade analytical solutions. The VP will collaborate closely with Front Office, Risk Management, Technology, and Data teams to enhance data infrastructure, improve data quality, and support the development and maintenance of key trading book risk models, including Value-at-Risk (VaR), Stressed VaR (sVaR), Sensitivity Analysis, and Stress Testing etc.

Requirements

Master’s degree or Ph.D. in Mathematics, Statistics, Computer Science, Data Science or a related quantitative discipline.
Minimum 3 years of hands-on experience working with AI and/or Data Analytics.
Strong programming skills in Python and experience working with large-scale structured and unstructured datasets.
Strong understanding of market risk methodology, such as VaR, sensitivities, risk factor modeling and stress testing.
Practical experience in statistics, data analytics or artificial intelligence and familiarity with model development lifecycle.
Excellent analytical, problem-solving, and communication skills.
Ability to work collaboratively with cross-functional teams and build effective relationships with stakeholders.

Responsibilities

Lead the design and implementation of Agentic AI and Generative AI solutions to automate and enhance market risk data processing, time series construction, and historical data backfilling.
Develop scalable AI-driven framework for data quality monitoring, anomaly detection, and data remediation.
Evaluate and incorporate emerging AI technologies to improve analytical workflows and operational efficiency.
Design and implement advanced statistical approaches to support evaluation, monitoring and continuous improvement of AI based models.
Build prototypes and production-ready analytical models utilizing large-scale financial datasets.
Work with model review and validation teams to ensure compliance with regulatory and firm governance standards applicable to both quantitative and AI models.
Collaborate with technology teams to ensure seamless integration of analytical solutions into production environment.
Present analytical findings, model results and strategic recommendations to senior management and key stakeholders.