Senior Data Scientist

Data scientists at Disney Direct-To-Consumer are the insights and modeling partners for the growth, content, marketing, product, and engineering teams at Disney+, Hulu and ESPN+. They use data to empower decision-makers with information, predictions, and insights that ultimately influence the experiences of millions of users worldwide. Scientists on the team build and productionize models that are used in marketing platforms and in-product every day. They provide scalable, persistent capabilities that are iteratively improved through direct interaction with cross-functional business partners. 

As a senior data scientist in the Retention and Engagement Modeling Intelligence Data Science team, you will be partnering closely with the Marketing, Subscriber Analytics, Commerce Product, and Engineering teams to develop models for tackling a multitude of exciting challenges, including churn and upgrade prediction, plan recommendation, discount optimization, signups and subscriber forecasting, causal inference, anomaly detection and much more! In this role you will also be working closely with non-technical business partners and executives, and it requires the use of analytical abilities, business understanding, and technical savvy to identify specific and actionable opportunities to solve business problems through data modeling. 

We are looking for someone with deep analytical and modeling expertise, a proven track record of thought leadership, and eagerness to drive impact. 

Responsibilities 

• Modeling: Design, build, deploy, and improve machine learning pipelines. Work end to end from data collection, feature generation and selection, algorithm development and tuning, visualization and monitoring of model results, and productionalization of pipelines. Work with partner teams to drive experimentation to test impact of models. 

• Complex analysis & Visualization: Develop comprehensive understanding of subscriber, playback, and payment data structures and metrics. Mine large data sets to identify opportunities for driving growth and retention of subscribers.  Development of prototype solutions, mathematical models, algorithms, and robust analytics leading to actionable insights communicated clearly and visually.  

• Partnership: Partner closely with business stakeholders to identify and unlock opportunities, and with other data teams to improve platform capabilities around data modeling, data visualization, experimentation and data architecture. 

Basic Qualifications 

• Bachelor’s degree in advanced Mathematics, Statistics, Data Science or comparable field of study 

• 5+ years of experience designing, building, and evaluating practical machine learning solutions 

• Strong coding experience in one (or more) data programming languages, including Python; additional experience with distributed computing tools like PySpark and SparkML or equivalent libraries a plus 

• Strong background in statistical & machine learning modeling: regression, classification, choice modeling, time series analysis, segmentation, dimensionality reduction, and other techniques 

• 5+ years experience with databases and data pulling tools (SQL, Hive) 

• Experience with version control tools such as git 

• Willingness to adapt in fast-paced and quickly growing work environment 

• Seasoned & resourceful problem solver who figures out how to get things done, even if it means navigating through ambiguity 

Preferred Qualifications 

• Master’s or Ph.D in Applied Mathematics, Computer Science, Statistics, Economics or related degree 

• Experience deploying data science pipelines at-scale in a production environment 

• Familiarity with MLOps best practices 

• Excellent analytical skills, advanced level of statistics knowledge 

• Demonstrated skill in selecting the right statistical or machine learning tools to solve a given problem 

• Ability to adapt quickly in a fast-moving environment with shifting priorities 

• Strong communication skills, for both technical and non-technical audiences 

• Ability to handle multiple tasks concurrently and in a timely manner 

• Familiarity with data platforms and applications such as Databricks, Jupyter Notebooks, Snowflake, Airflow, Github Actions 

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

• Familiarity with designing and analyzing A/B testing and other experiment types 

• Experience thinking strategically to interpret market and consumer information, preferably about a subscription service 

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