VP, Data Analytics & AI

Company

Federal Reserve Bank of San Francisco

We are the San Francisco Fed, public servants with a congressionally mandated mission to promote a sound and stable economy to support the lives of all Americans. We are a community-engaged bank, and we are committed to understanding and serving the vibrant, diverse people of the Twelfth District. That means we seek and appreciate new perspectives. We respect people for what they do and for who they are. We build opportunities to learn and grow. When you join the SF Fed, you become part of a team united in its purpose to promote an economy that works for everyone. We empower our people to balance their life and work responsibilities. That’s why we offer a flexible hybrid work model that allows you to collaborate with office colleagues on some days, and work from home on others.

Looking to help bring your leadership, data engineering and AI enablement skills to help build an exciting new team at the SF Fed? If yes – then read on!

We're looking for a Data and Analytics Services Head (VP) to set the overall vision, strategy and execution plan towards establishing Business Data and Analytics Products at the Federal Reserve system level across Data Engineering, Analytics, and Artificial Intelligence. You’ll partner and influence at the executive and senior leadership level and ensure excellence across product management, engineering and operations to delivery continued business value, while driving innovation through data analytics and insights.

Build and strengthen strategic partnerships across Federal Reserve System and overseeing large-scale data and analytics service delivery and operations. This role demands a strategic leader with a strong background in leading technology and business transformation managing extensive data delivery services with deep expertise in Data, Analytics and Artificial Intelligence technologies, and a commitment to establishing best-in-class data governance practices.

Highlights of Responsibilities

Strategic Leadership:

• Develop and communicate a compelling vision and strategy for the organization, aligning it with broader business objectives.
• Drive organizational transformation to embrace AI and Gen AI technologies, ensuring scalability to meet the demands of large-scale data services.

Team Leadership:

• Build and lead a strong team of data scientists, analysts, engineers, and other experts capable of managing extensive data operations.
• Foster a culture of innovation, collaboration, and continuous learning.

Data and AI Enablement:

• Define and implement strategies to leverage data as a strategic asset, focusing on scalability, efficiency, and business value for a large organization.
• Oversee the development and deployment of advanced analytics and AI solutions

Data Governance:

• Establish and enforce robust data governance practices, ensuring data quality, integrity, and security on a large scale.
• Collaborate with stakeholders to define and implement data standards, policies, and procedures that align with industry best practices.

Technology Stack and Infrastructure:

• Evaluate, select, and implement innovative technologies and tools that cater to a large-scale data and analytics organization.
• Ensure the scalability, security, and efficiency of the technology infrastructure.

Business Transformation:

• Drive business transformation initiatives to future-proof the organization at an enterprise level, considering the unique challenges and opportunities presented by large-scale data services.
• Collaborate with business units to identify and capitalize on opportunities for leveraging data and analytics for enhanced operational efficiency and strategic decision-making.

Stakeholder Management:

• Collaborate with C-level executives, business leaders, and cross-functional teams to align extensive data and analytics initiatives with overall business objectives.
• Act as a thought leader and advocate for the strategic importance of data and analytics on an enterprise scale.

Qualifications:

• Bachelor's degree in Engineering, preferably in a field related to computer science, data engineering, or a related field. Graduate degree (Master's or MBA) in Data Science, Business Analytics, or a related field preferable or relevant work experience.
• Proven leadership experience in progressively responsible roles within data and analytics for large organizations.
• Strong understanding of Generative AI, data management principles, data architecture, and AI technologies, including machine learning, natural language processing, computer vision, and predictive analytics.
• Strong knowledge of technology stacks covering comprehensive