Senior Human Resources Decision Science Consultant

The Walt Disney Company•Lake Buena Vista, FL

1d•Onsite

About The Position

At Disney, we’re storytellers. We make the impossible possible. We do this through utilizing and developing cutting-edge technology and pushing the envelope to bring stories to life through our movies, products, interactive games, parks and resorts, and media networks. Now is your chance to join our talented team that delivers unparalleled creative content to audiences around the world. Are you curious, creative, and love data? Do you love learning new things and collaborating with colleagues to solve hard, interesting problems? Imagine yourself as a Decision Scientist on the Human Resources (HR) Insights & Decision Science team in Disney Experiences (DX), where your natural curiosity to uncover analytical insights and trends will help ensure we make data-driven decisions within HR and across DX. In this role, you will be able to blaze new paths in this data-rich environment through statistical modeling, deep data analysis, and ongoing application of scientific methods to accelerate the company’s understanding of its employees. You will implement and contribute to the design of machine learning and statistical methods analyses that will turn data into information to maximize the Company’s investment in its employees. The right person for this role is self-directed and has exceptional analytical abilities, intellectual curiosity, and technical skills, a natural ability for storytelling using data, and is passionate about using statistical methods and visualizations to provide decision support for workforce-related issues. This position reports to the Manager, Human Resources Decision Science. This is a full-time role.

Requirements

Experience in using statistical, econometric, machine learning, or data mining techniques to inform model development and business decisions in a professional or academic setting.
Experience analyzing structured and unstructured data and developing machine-learning models using one or more data science programming languages (e.g., Python or R).
Experience building executive-ready presentations and translating complex statistical or predictive modeling results into clear, actionable insights for non-technical audiences.
Experience managing multiple analytical projects simultaneously, meeting defined deadlines, and operating effectively with minimal supervision.
Experience applying critical thinking and analytical judgment to solve ambiguous problems and rapidly learn or apply new analytical techniques as project needs evolve.

Nice To Haves

Experience developing dashboards and visualizations using tools such as Tableau and/or Cognos, and querying large-scale database environments (e.g., Snowflake, Redshift).
Experience applying supervised and unsupervised machine-learning algorithms and statistical methods, including clustering, PCA, linear and logistic regression, decision trees/random forests, boosted decision trees, forecasting, and model development.
Experience designing and executing in analytical workflows using platforms such as Dataiku, Databricks, and/or Alteryx.
Experience using Snowflake Cortex to leverage large language models (LLMs) and develop AI-powered applications for analyzing unstructured data.
Experience analyzing HR and employee data within enterprise systems such as SAP, SuccessFactors, and/or Workday.
Experience applying natural language processing (NLP) methods to extract insights from text data, including classification, topic modeling, sentiment analysis, or entity extraction.
Experience operationalizing data science solutions by deploying models into production environments and partnering with engineering or business teams to ensure scalability, reliability, and ongoing performance monitoring.

Responsibilities

Design, build, and implement accurate, sustainable, scalable, statistical models and advanced machine learning processes that support HR decisions, business processes, tools, or products.
Apply state-of-the-art machine learning, statistics, or data mining techniques to address key workforce-related questions and measure the causal impact of HR initiatives.
Develop scalable, reproducible, and efficient methods for data analysis and model development.
Build and work with large and complex data sets from multiple systems and outside data sources.
Consult with clients and analysts across the business, translating business objectives and analytical needs into repeatable analytical solutions.
Share technical knowledge and guide analysts throughout the HR Insights and Decision Science team
Present and explain results to technical and non-technical audiences through insightful visualizations that help tell a compelling story.