VP, Enterprise Data Services

Travel + Leisure Co.•Orlando, FL

About The Position

The Vice President of Enterprise Data Services will lead the Data Product Implementation Office (DPIO) and provide enterprise oversight for the Data Science function. This executive leader is accountable for coordinating and overseeing the implementation of data products across the organization; standardizing data definitions, data quality, and governance; capturing platform and capability requirements; and driving prioritization, resource allocation, and measurable value realization. The VP partners with business and technology leaders to scale trusted, governed data products and advanced analytics solutions that align with strategic objectives and improve operational and financial outcomes. The role will be instrumental in the execution of data and analytics strategies to drive business insights, decision-making, and value creation through key metrics that reflect the contribution of enterprise data, analytics, and data science to operational and financial business outcomes. This role is responsible for managing data products, overseeing a data literacy program, ensuring data governance, and providing leadership oversight for the Data Science team to deliver and operationalize predictive and prescriptive solutions.

Requirements

Bachelor's degree in Data Science, Business Analytics, Information Systems, Engineering or a related field; Master's degree preferred.
Certified Data Management Professional (CDMP) certification is a plus
Certification with one or more leading data platforms like Snowflake is a plus
Strong leadership and team management skills, with experience leading data literacy programs.
Excellent communication and presentation skills, with the ability to convey complex data concepts to non-technical audiences.
In-depth knowledge of data governance, data quality, and data management best practices.
Proven experience in data product management, data governance, or a related field.
Strong understanding of data analytics, data science, and data engineering principles.
Excellent leadership and project management skills, with a track record of successfully delivering complex data projects.
Strong communication and relationship-building skills, with the ability to engage and influence stakeholders at all levels.
Experience with data governance frameworks and standards.
Familiarity with agile methodologies and design thinking principles.
A good understanding of the concepts, methods and techniques used for diagnostic, descriptive, predictive analytics, master data management and stewardship practices
Database Management Systems that include Snowflake and Oracle
Programming languages like SQL, Python or R and notebooks like R Studio or Jupyter.
Data integration tools like Informatica or Talend.
Analytics and business intelligence tools like Microsoft Power BI or Tableau.
DSML platforms like DataBricks.or Snowflake
10+ years of experience in data and analytics, with a proven track record of translating data insights into business strategies.
Experience equivalent to the education requirement may be accepted in lieu of the education requirement.

Responsibilities

Lead the Data Product Implementation Office, setting the vision and strategy for data product implementation.
Develop and maintain a data product roadmap that aligns with the organization's strategic goals.
Collaborate with senior leadership to prioritize data product initiatives based on business value and impact.
Build and maintain strong relationships with key stakeholders, including business leaders, IT teams, and external partners.
Facilitate design workshops and working sessions to gather requirements and define project scope.
Communicate project progress, risks, and issues to stakeholders, ensuring transparency and alignment.
Establish and enforce data governance policies and procedures to ensure data integrity, security, and compliance.
Oversee data quality initiatives to ensure the accuracy and reliability of data used for decision-making.
Collaborate with cross-functional teams to define and implement data governance frameworks and standards.
Ensure that data governance practices align with industry best practices and regulatory requirements.
Lead efforts to improve data governance maturity across the organization, including data stewardship, data cataloging, and metadata management.
Provide strategic and operational oversight for the Data Science team, including demand intake, prioritization, staffing, and performance management.
Establish standards for model development, validation, monitoring, and documentation, including alignment to privacy, security, and regulatory expectations.
Partner with Data Engineering, IT, and platform teams to enable MLOps capabilities (deployment, CI/CD, observability, retraining, and incident response) and ensure solutions are production-ready.
Drive adoption and value realization of advanced analytics and AI solutions through stakeholder engagement, change management, and measurable outcomes.
Lead and mentor a team of data professionals, fostering a culture of collaboration and continuous improvement.
Provide guidance and support to team members, helping them develop their skills and achieve their career goals.
Promote best practices in data product development and implementation.
Oversee the design and implement a comprehensive data literacy program to enhance data-driven decision-making capabilities across the organization.
Oversee development of training materials, workshops, and resources to improve data literacy and analytical skills among employees at all levels.
Foster a culture of data-driven decision-making by promoting the value of data and analytics throughout the organization.