VP, Data Product Management

SMBC•Charlotte, NC

2d•Hybrid

About The Position

SMBC Group is a top-tier global financial group with a 400-year history, headquartered in Tokyo. It offers a diverse range of financial services and has a significant worldwide presence. In the Americas, SMBC Group provides commercial and investment banking services to its corporate, institutional, and municipal clients, connecting them to local markets and its global network. The role of VP, Data Product Management is focused on designing and transforming manual processes using AI and digital tooling, developing deliverables such as prototypes, analytics, and dashboards, and serving as a business analyst for data transformation, risk modeling, and financial reporting initiatives. The position also involves supporting production processes for CCAR systems, partnering with stakeholders to improve controls and efficiency, acting as a Scrum Master, and preparing documentation and training materials. Additionally, the role requires establishing frameworks for data validation and integration testing, ensuring platform reliability, and maintaining knowledge of the technology stack supporting model training.

Requirements

5+ years of total experience combining Business Analysis and hands-on software development experience within financial services or financial technology
Strong data analysis skills, including hands-on experience with SQL and python
Hands-on experience with ML/AI development tools (such as Azure ML, AWS SageMaker, PyTorch) and cloud computing platforms (AWS, Azure, Databricks, Snowflake)
Demonstrated hands-on transformation experience: you have directly helped design, build, or implement process and tooling changes (beyond coordination/PMO activities)
Self-driven, self-motivated, and able to operate independently while collaborating effectively in a squad/team environment
The candidate should be capable of understanding and solving highly complex problems, have excellent communication skills and have experience in financial services, preferably in the areas of commercial banking, investment banking and trading
Solid understanding of Capital Markets, preferably in Sales & Trading or Investment Banking
Experience working with trade data, position data, and reference data

Nice To Haves

Experience working in financial services with exposure to regulatory reporting and/or CCAR (or closely related stress testing processes)
Excellent written and verbal communication skills, with the ability to engage senior stakeholders

Responsibilities

Design and transform manual processes using AI and digital tooling (e.g., CoPilot, Power Automate, Power BI, Alteryx, and emerging AI-enabled tools)
Develop and influence deliverables directly: create prototypes, analytics, dashboards, and automations that accelerate decision-making and reduce manual work
Serve as business analyst for Data transformation, Risk Modeling and Financial Reporting initiatives, translating model development, risk reporting, financial reporting and regulatory requirements (e.g., CCAR) into clear user stories, process maps, and functional requirements
Support production processes for systems and workflows used in CCAR, including triage of issues, root-cause analysis, and coordination of fixes with Technology and business owners
Partner with Capital Planning SMEs, Technology, and key Risk and Finance stakeholders to identify pain points, define target-state workflows, and deliver solutions that improve controls, transparency, and efficiency
Serve as the squad’s Scrum Master: facilitate Agile ceremonies (stand-ups, refinement, planning, retrospectives), remove blockers, and help the team continuously improve delivery practices and velocity
Prepare documentation, training materials, and test artifacts (test scripts, scenarios, acceptance criteria) to enable consistent adoption across stakeholder groups
Establish frameworks for data validation, integration testing, and performance monitoring.
Ensure platform reliability and data integrity through collaboration with QA and engineering teams for continuous build and delivery (CI/CD) of features.
Plan and facilitate user acceptance testing and stakeholder sign-offs; coordinate release readiness and communications
Maintain working knowledge of the complete technology stack supporting Model training, including cloud computing, Machine Learning frameworks, and orchestration systems