Data Scientist, Applied AI and ML

Universal Orlando Resort believes in-person collaboration is key to our success. Many of our Team Members work in a hybrid capacity, contributing from the workplace a minimum of three days per week. There are also roles that require being on-site full time. Limited remote opportunities may be available within specific departments. You’ll learn more about this during the recruitment process.

JOB SUMMARY:

The Data Scientist, Applied AI/ML will work closely with a team of skilled data scientists to develop innovative capabilities that enhance guest experiences at our destinations and improve engagement with our digital products. This role requires a strong background in computer science, machine learning, and analytics. The individual will be responsible for designing, developing, and maintaining large-scale AI/ML systems aimed at both enhancing the guest experience, improving relevancy, and driving operational efficiencies. In addition to technical expertise, this role necessitates effective collaboration across the organization. The Data Scientist will need to understand business problems, identify, and integrate relevant data sources, support technology implementation, and communicate findings to senior leadership.

MAJOR RESPONSIBILITIES:

AI / ML System Design and Implementation

• Design and implement AI systems using large language models (LLMs) to enhance both guest interactions and internal operations.
• Optimize LLMs to meet the specific needs of guests and employees, ensuring relevant, personalized experiences and improved operational efficiency.
• Collaborate with data teams to ensure proper ingestion, training, and deployment of LLMs at scale for both guest and internal data sources.
• Stay current with LLM advancements to continually improve AI applications for both guest experiences and internal operations, ensuring scalability and impact.
  

Personalization and Recommender Systems

• Utilize guest data—both known and inferred—across their journey, from planning to on-property experiences, to deliver the right content at the right time.
• Develop machine learning models that utilize advanced techniques such as reinforcement learning, deep learning, and natural language processing (NLP) to deliver personalized guest experiences.
• Select and implement appropriate algorithms for classification, regression, and clustering tasks, optimizing for performance and scalability.
• Define and produce actionable deliverables that identify opportunities for improving guest experiences, which will be shared with internal stakeholders and decision-makers.
  

Analytics and Insights

• Use SQL and other data extraction tools to collect, manipulate, and analyze large datasets.
• Conduct advanced statistical analysis to better understand guest behavior and identify patterns or trends.
• Present analytical findings clearly and effectively to business stakeholders, aiding in data-driven decision-making.
• 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:

7 years of hands-on experience in data science, working with cross-functional teams to implement advanced analytics solutions in real-world applications.

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

Universal is not accepting unsolicited assistance from search firms for this employment opportunity. All resumes submitted by search firms to any employee at Universal Orlando via-email, the Internet or in any form and/or method without a valid written Statement of Work in place for this position from Universal Orlando HR/Recruitment will be deemed the sole property of Universal Orlando. No fee will be paid in the event the candidate is hired by Universal Orlando as a result of the referral or through other means.

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