CIB AI Strategy & Control Vice President

BBVA•New York, NY

4d•$150,000 - $190,000•Onsite

About The Position

The US AI & Data Team accelerates business transformation by turning data and Artificial Intelligence into trusted, scalable capabilities that deliver measurable value. It partners with business, technology, risk and operations teams to identify high-impact opportunities, develop and deploy data-driven and AI-enabled solutions, and support responsible adoption through data quality, governance, explainability and performance monitoring. The team aims to improve client experience, commercial effectiveness, operational efficiency and risk management across the organization. The Vice President leads the design, development and industrialization of data science and AI solutions that improve client engagement, commercial effectiveness, operational efficiency and risk management. The role combines analytical depth with business judgment to translate strategic priorities into scalable, governed and measurable data products. It is based in BBVA’s New York Office. Candidates must be eligible to work in the United States; BBVA will not pursue visa sponsorship for this position.

Requirements

At least 7 years of professional experience as a Data Scientist, Analytics Specialist, Machine Learning Engineer or in a comparable data-focused role.
Demonstrated experience delivering end-to-end analytical or AI solutions in complex, cross-functional environments, from problem definition through production deployment and value tracking.
Strong hands-on skills in Python and SQL, statistical analysis, machine learning, experimentation and data visualization.
Ability to work with large, imperfect data sets and communicate technical concepts clearly to non-technical audiences.
Bachelor's or Master's degree in Data Science, Statistics, Computer Science, Engineering, Mathematics, Economics or a related quantitative discipline.
Professional fluency in English.
Eligibility to work in the U.S.; visa sponsorship is not available.

Nice To Haves

Experience with cloud data platforms and MLOps is strongly valued.
Experience in financial services, regulated environments or risk-sensitive use cases is an advantage.

Responsibilities

Frame high-value business problems and define data science approaches, success criteria and measurable KPIs with business, product and operations stakeholders.
Build, validate and deploy predictive, optimization and machine learning models, and contribute to Generative AI and agent-based use cases where appropriate.
Translate data insights into clear recommendations and decision-ready narratives for senior stakeholders, including assumptions, limitations and expected impact.
Partner with Data for AI and AI Tech, Risk, Compliance and Operations to deliver reusable, scalable solutions and manage dependencies across initiatives.
Establish model documentation, monitoring and performance standards, ensuring accuracy, explainability, responsible AI and compliance with data and AI governance.
Support portfolio prioritization by assessing feasibility, data readiness, investment needs, value potential and adoption requirements; promote adoption through training and change management.