Internship - Data Science, Global Product and Pricing (Spring 2025)

Universal Destinations & Experiences Internship Program:

• Applications Close: June 28th, 2024, at 11:55PM ET. Submit your application as soon as possible - don't delay!

• Spring 2025 Program Dates: Approximately January 2025 - April 2025

JOB SUMMARY:

The Data Scientist Intern will be part of UDX's Global Product and Pricing team. The intern will train under the guidance of a data scientist in price optimization for admissions. The intern will learn end-to-end (systems, models, processes, and business) how admission prices are optimally generated and implemented.

MAJOR RESPONSIBILITIES:

• Learns the process, systems, models, and business rules in the optimization of admissions pricing at Universal Destinations & Experiences.

• Prototypes models for forecasting demand and optimizing prices of admissions.

• Creates forecasting models at the optimal level of disaggregation and fine-tunes regressors/parameters for optimal accuracy.

• Creates optimization models in dynamic programming and fine-tunes parameters for generating actionable price recommendations.

• Conducts data analysis and identifies pricing strategies to generate incremental revenue.

• Constructs hypotheses to test pricing strategies and implements, measures, and reports on pricing tests.

• Practices programming skills in Python, SQL; working with Tensorflow, Prophet, SciPy, NumPy libraries; working in AWS, Snowflake.

• As-Is and To-Be process mapping and analysis

• 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:

• In pursuit of an Graduate degree at an Accredited Institution.

• Recent graduates will not be eligible for this program.

• Minimum cumulative 2.8 GPA is required.

• An official transcript may be required upon request.

• Preferred majors include: Statistics, Operations Research, Data Science.

• Preferred completed coursework:

• Linear Programming

• Mixed-Integer Programming

• Probability

• Statistics

• Machine Learning

ADDITIONAL INFORMATION:

Preferable skills for success in role include but not limited to

• Excellent modeling skills in forecasting and optimization preferred.

• Preferred familiarity with Revenue Management, Dynamic Programming, Price Elasticity of Demand, Tensorflow, Prophet, SciPy, NumPy, AWS, Snowflake, PowerBI, and Excel.

• Must be efficient in Microsoft Office Programs including, but not limited to: Word, Excel, and PowerPoint.

• Strong interpersonal skills, problem-solving abilities and organization.

• Exceptional attention to detail.

• Superior written & verbal communication skills.

• Work in a fast-paced environment and adhere to deadlines.

• Ability to work autonomously and/or in teams.

• Consistent attendance.

Please note the following

• This internship will be a hybrid experience, based in our Orlando offices.

• Interns must be currently pursuing a degree at an accredited university, and must have a graduation date later than April 2025.

• Universal Orlando does not provide housing. Interns are responsible for their own housing and transportation.

• In addition to all of our internships being paid, you may be eligible for financial assistance towards housing if applicable. Specific details about eligibility would be provided at the time of offer.

• Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.

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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