Manager, Data Science

Department/Group Overview

The Disney Music Group (DMG) is the music hub for TWDC, encompassing all aspects of music commercialization and marketing: recorded music (Walt Disney Records and Hollywood Records), Disney Music Publishing, and Disney Concerts. DMG distributes music both physically and digitally, and also licenses music throughout the world in various forms of media including television, print, gaming, and consumer product.

Job Summary

As a member of DMG’s Data & Analytics team, the Manager, Data Science will lead development of advanced capabilities and tools that enable a deeper understanding of how content, marketing, and distribution strategies impact product performance. In this role, you will innovative solutions through research, experimentation, model development, and algorithm design.

The ideal candidate for this role possesses a blend of technical expertise and strong leadership skills. They have a proven track record of solving complex challenges in media and entertainment and excel at transforming data into strategic opportunities.

Responsibilities

• Lead development of analytical frameworks to address complex, high-value business problems across recorded music, publishing, and concerts. Develop mathematical models, measurement frameworks, and algorithms. Prototype solutions for implementation in analytic pipelines, tools, and operational workflows

• Establish robust experimental designs to assess the impact of content, product, and marketing strategies, delivering actionable and scalable insights

• Develop decision support tools that assist stakeholders in evaluating business opportunities. Build forecast and optimization models to quantify opportunity size, risks, and trade-offs

• Develop operational metrics to assess the health of brands, products, and campaigns. Employ machine learning, statistical analysis, and data mining methodologies to build out in-depth knowledge of success drivers, their interactions and contribution to overall business performance

• Provide technical leadership and mentorship to a team, fostering a culture of innovation and collaboration, and setting priorities to maximize impact in the organization

• Stay at the forefront of emerging data science techniques and technologies, recommending and implementing advancements that enhance the team’s capabilities

• Closely collaborate with DMG Data & Analytics team members and cross-functional stakeholders

• Partner with Technology teams on various projects, contributing to solution discovery, design, build and QA

Basic Qualifications:

• Minimum 8+ years of relevant data science experience

• Minimum 2+ years of management experience

• Proven experience in developing models and statistical analyses for business use cases in an industry setting. Demonstrated expertise in applying supervised and unsupervised learning techniques, including clustering, regression, and classification

• Experience with causal inference methods

• Proven track record in managing and executing full-cycle analytics projects

• Ability to draw insights and conclusions from data to inform model development and business decisions

• Experience manipulating large-scale datasets and interpreting data trends from multiple disparate sources

• Hands on experience with SQL and numerical computing languages such as PySpark/Python, R

• Experience data mining within distributed systems such as Databricks, Snowflake, Google BigQuery

• Proficient with data exploration and visualization tools such as Tableau, Looker, DOMO

• Strong time management with ability to work in a fast-paced environment across multiple priorities

Preferred Qualifications:

• Experience operationalizing data science solutions

• Familiarity with music streaming services (Spotify, Apple, Amazon Music, YouTube), social media platforms (TikTok, FB/Instagram, X) and emerging technologies (digital assistants/voice)

• A passion for music and entertainment industry data

Required Education

• Bachelor’s degree in an analytical field including Statistics, Mathematics, Physics, Computer Science, Engineering, or other related quantitative field. Master’s degree preferred