Machine Learning Opportunities at Disney+

Situation

Disney+ entered a competitive streaming market alongside major players like Netflix and Amazon Prime. With increasing demand for personalized experiences, the company needed to explore how Machine Learning (ML) and Big Data could support business growth, customer retention, and user satisfaction.

Task

My task was to assess Disney+’s business model and data environment, and recommend practical ML use cases aligned with strategic goals. I aimed to identify opportunities to improve decision-making, customer engagement, and content delivery using data-driven insights.

Action

• Mapped business goals to relevant ML techniques (e.g., personalization, churn prediction, streaming quality).

• Conducted a competitive benchmarking analysis of Netflix's ML and recommender systems.

• Applied the CRISP-DM framework to structure business understanding, data analysis, modeling, and deployment recommendations.

• Identified ethical risks in algorithmic bias and proposed data governance and fairness strategies.

• Developed insights on data sources (e.g., social media, viewing history, device usage) and how to use clustering and predictive modeling to inform user experience.

Result

• Delivered a comprehensive strategic report with machine learning use cases, business-technology alignment, and ethical considerations.

• Proposed a multi-layered data collection and personalization model for Disney+ using taste communities and content interaction patterns.

• Gained hands-on experience in applying business analysis principles to real-world streaming platforms.

• Recognized for a well-structured and strategic approach to integrating ML into business operations.

Skills Highlighted

• Business Requirements Analysis

• Data Strategy and Analytics

• Machine Learning Concepts for Business

• CRISP-DM Framework

• Benchmarking and Competitive Intelligence

• Ethical AI and Bias Mitigation

• Academic Research and Reporting

• Stakeholder Communication and Team Collaboration