JOB SUMMARY:

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.

MAJOR RESPONSIBILITIES:

AI / ML Technical Leadership and Solution Design

• 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.

Personalization and Recommender Systems

• 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.

Analytics, Experimentation, and Insights

• 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.

Technical Mentorship and Cross-Functional Leadership

• 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.

EDUCATION:

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

EXPERIENCE:

• 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.

Your talent, skills and experience will be rewarded with a competitive compensation package.

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