The requirements listed below are representative of the knowledge, skills, and/or abilities (KSAs) required: Must have proficiency with data mining, mathematics, machine learning, and statistical analysis Must have experience and proficiency using machine learning platforms (e.g., AzureML), process automation platforms (e.g., MS Power Automate, etc.), application development platform (e.g., Power Apps, etc.), data querying and scripting/programming tools (e.g., SQL, Python, etc.), business intelligence/data visualization software tools (e.g., Power BI, Tableau, etc.), and statistical modeling software applications (e.g., R, etc.) Proven strong PC skills including spreadsheets, databases, and presentation graphics software Demonstrated leadership ability and/or previous managerial experience Strong coaching/mentoring skills and Leadership experience in continuous improvement Strong critical thinking and creative problem solving skills Demonstrated superior conceptual thinking skills and the ability to work through complex problems Capable of communicating and expressing ideas clearly and concisely, in both written and oral formats Strong communication skills with the ability to convey complex findings to both technical and non-technical stakeholders Ability to work collaboratively in a team environment, work in a fast-paced environment and under changing conditions Demonstrated understanding of the Universal Destinations & Experiences (UDX) heritage and a commitment to change and excellence Willingness to support a 24/7/365 Universal Destinations & Experiences (UDX) operation, which includes periods of high demand (weekends, holidays, etc.) Reasonable accommodation may be made to enable individuals with disabilities to perform the essential functions. EDUCATION: Bachelor’s degree and Master’s Degree in industrial engineering, operations research, mathematics, statistics, computer science, decision science, management science, data science, data Analytics, or a closely-related field of study Doctoral degree in industrial engineering, operations research, mathematics, statistics, computer science, decision science, management science, data science, data analytics, or a closely related field of study is preferred.