Data Scientist, Workforce Analytics

JOB SUMMARY:

As a Team Member of Universal's Business Analytics and Industrial Engineering team, this role supports operations and planning for Workforce and Labor Analytics, focusing on forecasting labor demand and optimization of staffing. Duties include working with stakeholders and teams to define staffing problems and goals, then formulates and applies advanced analytical approaches (such as statistical modeling, forecasting, machine learning, mathematical optimization, and decision analysis), to drive staffing optimization. This role produces analytical models, tools, and processes, to improve the effectiveness and drive incremental business value for the company.

MAJOR RESPONSIBILITIES:

• Formulate and apply advanced analytical approaches, such as causal and time series forecasting modeling, econometric methods, machine learning modeling, mathematical optimization, to name a few, for complex analyses, predictions and problem-solving. Perform data and error analysis to improve models.
• Assist in collecting, cleaning, and organizing data. Analyze large structured and unstructured datasets to identify trends, patterns, and insights. Identify causes of variability, test new features, and integrate into code.
• Use business intelligence tools to create and maintain clear and compelling reporting and visualizations to communicate complex findings to technical and non-technical stakeholders.
• Explore new, state-of-the-art analytical tools, methodologies, and technology that can be leveraged by our team.
• Lead and manage interns, co-ops, Analysts, Engineers and/or Associate Data Scientists.
• Understand and actively participate in Environmental, Health & Safety responsibilities by following established UO policy, procedures, training and team member involvement activities.
• Performs other duties as assigned.
  
  

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, required.
• Master's degree or above in similar related field preferred.
  
  

EXPERIENCE:

• 5+ years experience formulating and applying advanced analytical approaches required.
• 3+ years experience in analytical model design, development, and deployment required; will consider equivalence in education and experience
• Coding, programming and optimization experience (Python, SQL, Azure / Azure Machine Learning, and/or CPLEX preferred)
• Experience in labor and workforce analytics a plus
• Experience in theme parks, resorts, retail/dining/entertainment venues, or other hospitality related industry a plus.
  
  

ADDITIONAL INFORMATION:

• Develops analytical and predictive models and solutions for operating divisions within Universal Destinations & Experiences (UDX) domestic or international parks, to support key decisions and drive incremental business value.
• Strong foundation in advanced analytical modeling, programming, and data analysis
• Solves real-world problems using data-driven insights
• Translates and communicates complex data into actionable insights.
• Plays a crucial role in driving data-driven decision-making processes and contributing to the overall success of the organization.
• Supports and guides Analysts, Engineers and Associate Data Scientists on the use of advanced model development methodologies, as applicable
  
  

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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