Vice President, Data Management & Quantitative Analysis

Job description

At BNY, our culture allows us to run our company better and enables employees’ growth and success. As a leading global financial services company at the heart of the global financial system, we influence nearly 20% of the world’s investible assets. Every day, our teams harness cutting-edge AI and breakthrough technologies to collaborate with clients, driving transformative solutions that redefine industries and uplift communities worldwide.

Recognized as a top destination for innovators, BNY is where bold ideas meet advanced technology and exceptional talent. Together, we power the future of finance – and this is what #LifeAtBNY is all about. Join us and be part of something extraordinary. We’re seeking a future team member for the role of Vice President – Data Governance & Data Modeling to join our Asset Servicing team. This role is located in NYC, NY.

In this role, you’ll make an impact in the following ways: We are seeking a Vice President – Data Governance & Data Modeling to support enterprise data management and governance priorities. This role requires a candidate with a Computer Science background, strong hands-on data modeling experience, and practical knowledge of data governance within the finance industry.

Key Responsibilities

Design and maintain conceptual, logical, and physical data models. Support data governance activities including data quality, lineage, metadata, and stewardship. Partner with business and technology teams to define data standards and controls. Help identify and remediate data issues to improve consistency, integrity, and usability. Contribute to scalable data solutions that support reporting, analytics, and operational needs.

To be successful in this role, we’re seeking the following: Bachelor’s degree or equivalent combination of education and experience. 5+ years of experience in the finance industry. Hands-on experience with data modeling and database programming (PLSQL) Strong understanding of data governance, including data quality, lineage, metadata, and controls. Familiarity with applied AI and its use in data, analytics, or governance processes.

Strong analytical, problem-solving, and communication skills. Experience in financial services data domains such as client, product, transaction, or reference data. Familiarity with data governance or metadata management tools. Experience working in a regulated environment.

Responsibilities

Lead the design and development of data solution architectures to support AI initiatives. Collaborate with data scientists to groom user stories, ensuring alignment with business needs. Oversee the implementation and maintenance of data management systems, including data governance and quality assurance processes. Develop and execute data-centric strategies to drive business growth and efficiency. Foster a data-driven culture by promoting best practices and providing guidance to teams across the organization.

Stay updated with industry trends and emerging technologies in data management and AI. Mentor and guide a high-performing team of data professionals, fostering a collaborative and innovative work environment. Ensure data security and privacy compliance, adhering to regulatory standards and internal policies. Partner with business stakeholders to understand their data requirements and translate them into actionable plans.

Qualifications

Advanced degree in Computer Science or a related field, with a strong background in data management and exposure to AI solutions. Minimum of 7 years of experience in data-centric roles, with a proven track record of leading complex data projects. Demonstrated expertise in data architecture design, data modeling, and data engineering principles. Strong leadership and communication skills, with the ability to influence and collaborate across diverse teams.

Experience working with large-scale data platforms and tools, including cloud-based solutions. Proficiency in data visualization and storytelling techniques to communicate complex data insights. Familiarity with regulatory requirements and data privacy laws, ensuring compliance in data management practices. Ability to stay updated with industry trends and emerging technologies, driving innovation within the organization.

Excellent problem-solving and analytical skills, with a data-driven mindset. A passion for data-centric solutions and a commitment to driving business value through data-informed decision-making.