Executive Director - Product Management & Data

Las Vegas Sands Corp.•Dallas, TX

22h

About The Position

The primary responsibility of the Executive Director – Product Management & Data is to build and lead our product, data science, and analytics vision for next‑generation customer experience across the casino ecosystem. This role owns the strategic integration of product management, data platforms, and applied data science to drive intelligent, personalized, and compliant customer experiences at scale. The Executive Director – Product Management & Data will be responsible for the entire lifecycle of our casino management, customer experience and data products, from concept and development to launch and ongoing optimization. This leader will: lead a talented team of product managers and work closely with cross-functional teams across engineering, design, marketing, and operations to create and enhance products that drive player engagement, operational efficiency, and revenue growth. oversee the application of data science, advanced analytics, experimentation, and machine‑learning models across the product portfolio to influence customer engagement, operational efficiency, and revenue growth. champion a customer‑centric mindset while leveraging advanced technologies such as AI/ML, real-time data platforms, marketing automation, and behavioral analytics to create meaningful, cohesive, and profitable customer journeys. All duties are to be performed in accordance with departmental and Las Vegas Sands Corp.’s policies, practices, and procedures. All Las Vegas Sands Corp. Team Members are expected to conduct and carry themselves in a professional manner at all times. Team Members are required to observe the Company’s standards, work requirements and rules of conduct.

Requirements

At least 21 years of age.
Proof of authorization to work in the United States.
Bachelor’s degree in Business, Computer Science, Data Science, Marketing, or related field; MBA or advanced technical degree preferred.
Must be able to obtain and maintain any certification or license, as required by law or policy.
10+ years of experience in modern enterprise software development, including 5+ years in loyalty, customer experience, digital engagement, or data‑driven personalization roles.
Strong understanding of casino operations, patron lifecycle, loyalty programs, offer management, and gaming regulatory environments.
Experience working with Casino Management Systems (CMS), hotel/resort systems, digital apps, or loyalty ecosystems.
Deep knowledge of customer behavior patterns, segmentation methods, and gaming‑specific engagement levers.
Strong fluency with data platforms, including customer data platforms (CDP), DMPs, data warehouses, identity graphs, and real‑time data pipelines.
Strong understanding of statistical modeling, supervised and unsupervised learning, feature engineering, and model evaluation techniques.
Demonstrated experience operationalizing models in partnership with engineering teams, including batch and real‑time inference use cases.
Familiarity with model risk management, bias detection, explainability, and ethical AI practices, particularly in regulated industries.
Proficiency in translating complex analytical insights into executive‑level narratives, product decisions, and measurable business impact.
Expertise in customer identity resolution, multi‑source data integration, and cross-channel profiling.
Understanding of SQL basics, data modeling concepts, data governance, and analytics workflows (no coding required).
Demonstrated experience partnering deeply with engineering, architecture, and data science teams to define technical requirements and roadmap priorities.
Working knowledge of AI/ML concepts.
Experience with marketing automation, journey orchestration, and rules‑based or ML‑driven offer optimization.
Understanding of model lifecycle processes, A/B testing, experimentation frameworks, and performance measurement.
Familiarity with responsible AI, ethical data use, and privacy‑by‑design principles.
Proven success leading cross-functional teams through product discovery, delivery, and scaling.
Strong understanding of SDLC, Agile methodologies, and modern product operating models.
Experience with product tools such as JIRA, Confluence, Figma, or equivalents.
Ability to translate complex business opportunities into actionable user stories, use cases, and product requirements.
Excellent communication, stakeholder management, and executive storytelling capabilities.
Demonstrated ability to manage competing priorities in a fast-paced, highly dynamic environment.
Track record of driving outcomes through influence, collaboration, and strategic thinking.
Strong interpersonal skills with the ability to communicate effectively and interact appropriately with management, other Team Members and outside contacts of different backgrounds and levels of experience.

Nice To Haves

MBA or advanced technical degree preferred.

Responsibilities

Define and communicate a clear product vision, strategic direction, and multi‑year roadmap.
Lead end‑to‑end product lifecycle activities including discovery, requirements, prioritization, launch, and iteration.
Collaborate cross‑functionally with engineering, design, analytics, marketing, operations, and business stakeholders to deliver high‑quality products.
Develop and manage product goals, KPIs, and performance metrics to ensure measurable business and customer impact.
Define and lead the data science vision and roadmap aligned to product strategy, customer experience, and business outcomes.
Build, mentor, and scale high‑performing data science and advanced analytics teams, including applied ML, experimentation, and decision science capabilities.
Oversee the development, deployment, and lifecycle management of predictive models, segmentation models, propensity scoring, and optimization algorithms used across marketing, loyalty, and gaming operations.
Establish standards for model governance, performance monitoring, explainability, and responsible AI, ensuring compliance with regulatory and data‑privacy requirements.
Partner with engineering and data platform teams to ensure production‑grade model deployment, real‑time inference, and scalable analytics pipelines.
Champion a culture of experimentation, A/B testing, causal inference, and data‑driven decision making across product and business teams.
Drive adoption of modern technologies such as AI/ML, real‑time data streaming, identity resolution, and API‑first architectures to advance product capabilities.
Partner with engineering, architecture, and data platform teams to define technical requirements, integration strategies, and architectural standards that ensure reliability, scalability, and security.
Use data science, advanced analytics, A/B testing, experimentation frameworks, and predictive modeling to improve personalization, decisioning, and customer engagement.
Leverage automation, journey orchestration, and ML‑driven optimization engines to enhance omnichannel experiences.
Stay informed about emerging technology platforms, gaming ecosystem innovations, and market shifts that could influence product direction.
Build, mentor, and grow a high‑performing product management team; cultivate a culture of ownership, excellence, and innovation.
Coordinate product strategy alignment with executive leadership, field operations, and commercial teams.
Engage with customers, internal stakeholders, and partners to gather feedback and validate direction.
Maintain product governance discipline through structured planning, communication, and progress tracking.
Stay informed about industry trends, market shifts, and emerging technologies that may influence product direction.
Ensure compliance with applicable regulatory, data governance, and operational requirements.
Perform job duties in a safe manner.
Attend work as scheduled on a consistent and regular basis.
Perform other related duties as assigned.