**Lead Data Scientist, Subscriber Core Data Science**


Data scientists at Disney 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 models, perform statistical analysis, and create visualizations to provide scalable, persistent capability that is iteratively improved through direct interaction with cross-functional business partners.


As a lead data scientist in the Subscriber Core Data Science team, you will be partnering closely with the Subscriber Analytics team, Finance, Business Operations, Commerce Product and Engineering teams to develop models for tackling a multitude of exciting challenges, including customer lifetime value estimation, signups and subscribers forecasting, fraud prevention and mitigation, payment optimization, and more.


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


**Responsibilities**


**Modeling** : Design, build and improve machine learning models. Work end to end from data collection, feature generation and selection, algorithm development, forecasting, visualization and communicating of model results. Collaborate with engineering to productionize models. Drive experimentation to test impact of model based optimization.


**Deep analysis** : Develop comprehensive understanding of subscriber and payment data structures and metrics. Mine large data sets to identify opportunities for driving growth and retention of subscribers.


**Visualization of Complex Data sets** : 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**


Masters degree in a quantitative field (e.g. Computer Science, Engineering, Mathematics, Physics, Operations Research, Econometrics, Statistics)


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


7+ years of experience with statistical programming language (e.g. Python, Spark, PySpark) and database languages (e.g. SQL)


**Preferred Qualifications**


Doctorate's degree in a quantitative discipline


Excellent analytical skills, advanced level of statistics knowledge


Strong expertise with Python and libraries such as scikit-learn, SciPy


Familiarity with Bayesian modeling and probabilistic programming packages such as PyMC


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


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


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


Demonstrated skills in selecting the right statistical tools given a data analysis 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, including large and complex ones


Demonstrated leadership experience, including people and project management


**Job ID:** 7113351420220130

**Location:** Santa Monica,California

**Job Posting Company:**
The Walt Disney Company and its Affiliated Companies are Equal Employment Opportunity employers and welcome all job seekers including individuals with disabilities and veterans with disabilities. If you have a disability and believe you need a reasonable accommodation in order to search for a job opening or apply for a position, email Candidate.Accommodations@Disney.com with your request. This email address is not for general employment inquiries or correspondence. We will only respond to those requests that are related to the accessibility of the online application system due to a disability.