Senior Vice President, Data Management & Quantitative Analysis Manager

In this role, you’ll make an impact in the following ways: Apply quantitative techniques from applied mathematics, statistics, econometrics, and risk modeling to solve business problems, assess risk, and generate insights that support decision-making across Risk & Compliance. Work on AI,GenAI,and machine learning use cases, using modern data science approaches for document intelligence, summarization, classification, knowledge extraction, intelligent search, workflow automation, and advanced analytics. Design and deliver scalable digital solutions by contributing across the full solution lifecycle, including ideation, development, testing, deployment, and continuous improvement, in partnership with business and engineering teams. Build and enhance data pipelines, dashboards, UI/UX and reporting solutions using Python, SQL, APIs, and enterprise platforms, working with both structured and unstructured data. Support data-driven transformation by improving processes, strengthening controls, and building hands on skills across analytics, data, engineering, automation, and emerging technologies Build and operationalize a centralized calculations service (rules, versioning, traceability) to ensure consistency, reproducibility, and audit-readiness across dashboards and reports. Build and govern a comprehensive metadata program—including catalog, lineage capture, classification, ownership (RACI), stewardship, and approval workflows—to improve discovery, traceability, and audit-readiness. Elevate data quality through critical data element (CDE) governance, validation rules, profiling, anomaly detection, and proactive remediation workflows; publish data quality scorecards and ownership. Provide executive-ready data health reporting and platform metrics that link infrastructure performance to business outcomes, risk posture, and regulatory commitments; maintain clear decision logs and evidence packs. Align platform strategy with BNY’s strategic pillars—be more for our clients through usable data products, run our company better with automation and controls, and power our culture through collaboration and standards. To be successful in this role, we’re seeking the following: 8-10 years in in data architecture, platform engineering, analytics or data product leadership; experience in financial services and Risk/Compliance domains strongly preferred. Strong understanding of risk and compliance frameworks (e.g., KRIs/KCIs, RCSA, issues/actions, surveillance, regulatory reporting) and ability to map them to measurable analytics. Proven expertise in enterprise data design (dimensional/normalized models), canonical data forms, vectorization/embeddings, semantic layers, and distributed data systems. Hands-on experience with metadata cataloging, lineage, data governance, and access controls across regulated environments. Familiarity with AI/ML platform components (feature stores, embedding/vector databases, model registries, monitoring/explainability) and MLOps/DataOps practices. Demonstrated track record delivering executive-grade dashboards and reporting at enterprise scale based on understanding of user journeys Proficiency with SQL, data warehousing/data lakes, streaming, orchestration, and observability tools; familiarity with Python and ML pipelines is advantageous. Excellent communication and stakeholder management skills—able to translate technical concepts into business outcomes and influence senior leaders. Intellectual curiosity, enthusiasm, and adaptability to rapidly assimilate new information and operate with a strong delivery focus in a fast-paced environment. Bachelor's degree required; advance degree in a quantitative areas like business, finance, engineering, or related disciplines; relevant industry certifications or qualifications are a plus.