“We create happiness.” That’s our motto at Walt Disney Parks and Resorts, and it permeates everything we do. At Disney, you’ll help encourage that magic by enabling our company to push the limits and build the never-before-seen! Are you ready to join this team and make an impact?
Disney Experiences (DX) is a world-class entertainment and technology leader. Walt’s passion was to innovate continuously and push the boundaries of what is possible, which remains central in our business today. Uniting each endeavor is a commitment to creating and delivering unforgettable experiences, and we’re constantly looking for new ways to enhance these exciting experiences for our guests.
As a Sr. Data Scientist, you will lead the delivery and deployment of machine learning models, supporting insightful and innovative predictive maintenance across our attractions. We work closely with internal partners to deliver world-class guest experiences with interactive & data systems across Disney Experiences.
What You’ll Do
- Design and implement robust, end-to-end machine learning pipelines that drive real-world impact.
- Collaborate closely with data scientists and ML engineers to optimize model performance and streamline training workflows.
- Deploy and monitor models in production using MLOps tools such as Airflow, Kubeflow, Docker, Kubernetes, and leading cloud platforms.
- Analyze system performance and troubleshoot deployment issues to ensure seamless model operation in production environments.
- Partner with IT and DevOps teams to integrate ML solutions into existing infrastructure with minimal disruption.
- Continuously monitor model health and performance, ensuring alignment with business benchmarks and SLAs.
- Manage compute and storage resources efficiently to support scalable model training and inference.
- Implement automated testing frameworks to validate model accuracy, reliability, and readiness for deployment.
- Mentor team members on MLOps tools and best practices, fostering a culture of collaboration and continuous improvement.
- Stay current with the latest advancements in data science, machine learning, and MLOps and apply them to solve complex challenges with innovation and agility.
Required Qualifications & Skills
- Minimum of 5 years of experience with data analytics and modeling using TensorFlow or PyTorch.
- Minimum of 3 years of hands-on experience deploying ML models into production environments.
- Proven experience with cloud-based ML platforms (e.g., AWS SageMaker, GCP Vertex AI, Databricks).
- Strong understanding of the model development lifecycle and MLOps practices.
- Proficiency in Python and deep learning algorithms (e.g., autoencoders, transducers).
- Experience with version control systems such as GitHub or GitLab.
- Familiarity with data visualization and monitoring tools (e.g., Splunk, Plotly, Tableau).
- Ability to communicate complex technical concepts in a clear and accessible manner.
- Experience using Atlassian tools like Jira and Confluence.
Preferred Qualifications & Skills
- Knowledge of software development lifecycle (SDLC) and QA processes.
- Experience with anomaly detection and/or predictive maintenance solutions.
- Proficiency with Docker and Kubernetes.
- Experience setting up CI/CD pipelines and using workflow orchestration tools like Airflow.
- Understanding of object-oriented software design patterns.
Required Education
Bachelor’s degree in Mathematics, Statistics, Data Science, or a related field—or equivalent work experience.
Preferred Education
Master’s degree in Mathematics, Statistics, Data Science, or a related discipline.
#DISNEYTECH
The hiring range for this remote position is $132,200.00 to $177,300.00 per year, which factors in various geographic regions. The base pay actually offered will take into account internal equity and also may vary depending on the candidate’s geographic region, job-related knowledge, skills, and experience among other factors. A bonus and/or long-term incentive units may be provided as part of the compensation package, in addition to the full range of medical, financial, and/or other benefits, dependent on the level and position offered.
