Trading Book Data and Analytics

SMBC Group is a top-tier global financial group. Headquartered in Tokyo and with a 400-year history, SMBC Group offers a diverse range of financial services, including banking, leasing, securities, credit cards, and consumer finance. The Group has more than 130 offices and 80,000 employees worldwide in nearly 40 countries. Sumitomo Mitsui Financial Group, Inc. (SMFG) is the holding company of SMBC Group, which is one of the three largest banking groups in Japan. SMFG’s shares trade on the Tokyo, Nagoya, and New York (NYSE: SMFG) stock exchanges. In the Americas, SMBC Group has a presence in the US, Canada, Mexico, Brazil, Chile, Colombia, and Peru. Backed by the capital strength of SMBC Group and the value of its relationships in Asia, the Group offers a range of commercial and investment banking services to its corporate, institutional, and municipal clients. It connects a diverse client base to local markets and the organization’s extensive global network. The Group’s operating companies in the Americas include Sumitomo Mitsui Banking Corp. (SMBC), SMBC Nikko Securities America, Inc., SMBC Capital Markets, Inc., SMBC MANUBANK, JRI America, Inc., SMBC Leasing and Finance, Inc., Banco Sumitomo Mitsui Brasileiro S.A., and Sumitomo Mitsui Finance and Leasing Co., Ltd. The anticipated salary range for this role is between $152,000.00 and $195,000.00. The specific salary offered to an applicant will be based on their individual qualifications, experiences, and an analysis of the current compensation paid in their geography and the market for similar roles at the time of hire. The role may also be eligible for an annual discretionary incentive award. In addition to cash compensation, SMBC offers a competitive portfolio of benefits to its employees. Role Description 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. Role Objectives 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. Qualifications and Skills 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. #LI-RCH SMBC’s employees participate in a Hybrid workforce model that provides employees with an opportunity to work from home, as well as, from an SMBC office. SMBC requires that employees live within a reasonable commuting distance of their office location. Prospective candidates will learn more about their specific hybrid work schedule during their interview process. Hybrid work may not be permitted for certain roles, including, for example, certain FINRA-registered roles for which in-office attendance for the entire workweek is required. SMBC provides reasonable accommodations during candidacy for applicants with disabilities consistent with applicable federal, state, and local law. If you need a reasonable accommodation during the application process, please let us know at .