Data Scientist - Universal Orlando

Orlando, FL

Job Category: Predictive Analytics Industry: Entertainment and Media Annual Salary: commensurate with experience

Design, develop and evaluate advanced predictive and machine learning models with a focus on the personalization and optimization of marketing tactics.  Analyze and extract relevant information about guest behaviors and preferences from both structured and unstructured data to better understand marketing opportunities. Help define and optimize segmentation strategy using a variety of techniques, ranging from statistical analysis to complex data mining and modeling. Conduct advanced analysis on various marketing efforts to gauge performance, impact and effectiveness against the desired results. Deliver clear and compelling findings with data visualization tools and presentations that inform and inspire internal stakeholders to make better business decisions. Collaborate with colleagues in Marketing Operations and IT to infuse predictive analytics into customer touchpoints driving increased relevance and business performance.





·Develops segmentation, propensity and look-a-like modeling of individuals across known, identified and anonymous audiences



·Mine data (both structured and unstructured) to detect patterns, opportunities and insights that drive our personalization strategy



·Create the analytics to leverage known, inferred and appended information about individuals to facilitate the right content, at the right time, across a guest’s planning, shopping, fulfillment and on-property experience.

·Create a comprehensive understanding of consumer behaviors and attributes that drives strategy, improves the customer experience and generates revenue.




·Define and produce deliverables that identify opportunities to shape consumer experiences and that inform and inspire internal stakeholders and decision makers.


·Understand and actively participate in Environmental, Health & Safety responsibilities by following established UO policy, procedures, training and team member involvement activities.



·         Perform other duties as assigned.



SCOPEThis role is responsible for the design and management of modeling practices and segmentation that incorporate demographic and behavioral data from CRM systems, online tracking data and 3rd party enhanced data, in partnership with internal marketing teams, to enhance understanding and increase value by application of actionable segmentation and models.


  • Experience leveraging predictive modeling, big data analytics, exploratory data analysis and machine learning to drive significant business impact
  • Expert knowledge programming in R or Python
  • Capable of interacting with relational databases through SQL
  • Ability to manipulate unstructured data to form insights about the business
  • Understanding of big data technologies Hadoop and Hbase
  • Familiar with visual analytic tools such as Tableau
  • Ability to paint a picture through analytics that will enhance and determine business decisions
  • Previous experience with marketing, media and customer segmentation strategy
  • Demonstrated a willingness to both teach others and learn new techniques
  • Ability to handle multiple projects required and work independently in a deadline oriented environment
  • Desire to work in a fast paced environment required


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

Consistent attendance is a job requirement.

:  Master’s degree and/or Certificate in Statistics/Analytics is required.

EXPERIENCE3-5 years prior hands-on experience in data science.  Experience programming with statistical modeling tools to fuel and deliver marketing personalization.  Strong familiarity with manipulating and mining unstructured data to transform business decisions that impact the bottom line.  Experience leveraging visual analytics to create a seamless and inspirational story that inspire and inform business leaders with the necessary knowledge to drive revenue and customer loyalty. 

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