Lead HR Decision Scientist

Job Summary:

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 to learn new things and collaborate with colleagues to solve hard and interesting problems? Imagine yourself as a Lead Decision Scientist on the Decision Science and Engineering team in People Insights where your natural curiosity for discovering analytical insights and trends will help ensure we are making data-driven decisions within Human Resources (HR) and across The Walt Disney Company. 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.

Responsibilities:

• Design and implement accurate, sustainable, scalable, complex 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 analyses 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 provide guidance to analysts throughout People Insights and HR

• Present and explain results to technical and non-technical audiences through insightful visualizations that help tell a compelling story.

Basic Qualifications:

• 3+ years of proven experience in using statistical, econometric, machine learning or data mining techniques to inform model development and business decisions in a professional or academic setting.

• Demonstrated proficiency in analyzing data and developing machine-learning models in one or more data science programming language such as R or Python

• Strong knowledge of supervised and unsupervised machine learning algorithms, statistical methods, forecasting, and model building (e.g. Cluster Analysis, PCA, Linear and Logistic Regressions, Decision Trees/Random Forests, Boosted models, Structural Equation Modeling)

• Exceptional storytelling / presentation-building skills, including the ability to translate complex statistical concepts into simple and actionable insights.

• Self-motivated, strong project management skills, and demonstrated ability to meet deadlines with minimal supervision.

• Critical thinking skills born out of a deep intellectual curiosity that drives a healthy appetite for learning and an open mind to pick up new analytical techniques as required.

Preferred Qualifications:

• 5+ years of proven 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 with leading and developing others.

• Experience with analytic workflow software such as Dataiku, Databricks, or Alteryx.

• Experience with HR / employee data (SAP, Success Factors, Workday).

• Experience with visualization tools, such as Tableau and/or Cognos, or large database environments (e.g. Snowflake, RedShift).

• Proven experience leveraging natural language processing methods.

• Experience fully integrating data science solutions into the business and operationalizing ML models.

Required Education

• Advanced degree (Master’s or above) in Statistics, Economics, Computer Science, Engineering, Mathematics, Analytics / Business Analytics, or a related quantitative field