Principal Data Scientist, Applied AI/ ML

Universal Orlando•Orlando, FL

About The Position

The Principal Data Scientist, Applied AI/ML serves as the technical lead for complex AI/ML (Artificial Intelligence/Machine Learning) initiatives that enhance guest experiences and improve engagement with digital products. This role is responsible for shaping solution design, guiding model development and deployment, and partnering with cross-functional teams to translate business needs into scalable, production-ready data science solutions. The role also provides technical mentorship and sets best practices for applied AI/ML across the organization.

Requirements

9+ years of hands-on experience in data science, working with cross-functional teams to implement advanced analytics solutions in real-world applications; or equivalent combination of education and experience.

Nice To Haves

Master’s degree in a quantitative field such as Statistics, Data Science, Computer Science, Economics, Analytics, or Econometrics is preferred.

Responsibilities

Lead the technical design of scalable AI/ML solutions, including large language model (LLM) applications, recommendation systems, predictive models, and decisioning frameworks.
Define model development standards, evaluation frameworks, and best practices for deployment, monitoring, and lifecycle management.
Guide cross-functional teams through the end-to-end development of AI/ML solutions from problem definition through production implementation.
Evaluate emerging AI/ML methods and technologies and recommend approaches that improve performance, scalability, and business impact.
Ensure AI/ML solutions are designed with appropriate controls for reliability, explainability, maintainability, and responsible use.
Lead the development of personalization and recommendation capabilities using guest data across the full guest journey.
Design and apply advanced machine learning techniques, including deep learning, NLP, reinforcement learning, LLMs, and generative AI, where appropriate based on the business problem.
Select and guide the implementation of algorithms for ranking, classification, regression, clustering, and optimization.
Partner with product, engineering, and analytics teams to operationalize models and integrate outputs into digital products and business processes.
Establish testing and measurement approaches to assess model effectiveness and continuously improve performance.
Use SQL and advanced analytical tools to extract, transform, and analyze large and complex structured and unstructured datasets.
Apply statistical analysis, experimentation, and causal inference to evaluate initiatives and quantify business impact.
Translate analytical findings into clear recommendations for technical and business stakeholders.
Define success metrics, KPIs, and measurement strategies that align AI/ML initiatives to business objectives.
Provide technical mentorship and guidance to data scientists through model reviews, design reviews, and coaching.
Promote best practices in coding, experimentation, documentation, reproducibility, and model governance.
Influence roadmap planning and prioritization by identifying high-value AI/ML opportunities and technical dependencies.
Serve as a subject matter expert for applied AI/ML and provide technical leadership across teams.
Understands and actively participates in Environmental, Health & Safety responsibilities by following established UO policy, procedures, training and team member involvement activities.
Performs other duties as assigned.