Data Scientist

About the Role and Team

Data scientists at Direct to Consumer are the insights and modeling partners for the growth, content, marketing, product, and engineering teams at Disney+, Hulu, ESPN+, and Star+. 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 multi-functional business partners.

As a Data Scientist I, you will be partnering closely with the Content, Programming, Marketing, Subscriber Analytics, Engagement Analytics, Finance, and Engineering teams to develop machine learning and statistical models for solving a multitude of exciting challenges. In this role you will also be working very closely with company executives, and it requires the use of analytical abilities, business understanding, and technical savviness to identify specific and actionable opportunities to tackle existing business problems through data modeling.

Responsibilities include:

• Modeling:
  Design, build and improve machine learning models. Work end to end from data collection, feature generation and selection, algorithm development, visualization and presenting model results. Collaborate with engineering to product ionize models. Drive experimentation to test impact of model-based optimization.
• Deep Analysis:
  Develop comprehensive understanding of subscriber engagement patterns. Mine large data sets to find 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:
  We partner closely with business collaborators to identify and unlock opportunities, and with other data teams to improve platform capabilities around data modeling, data visualization, experimentation, and data architecture.

• Strong coding experience in SQL and one (or more) data programming languages like Python/R, additional experience with scientific libraries like Num Py, Pandas, or equivalent libraries a plus
• Proficient in analyzing data and developing ML models using Python (with ML frameworks like Tensor Flow, scikit-learn, etc.)
• Experience and knowledge in statistical modeling: regression, classification, time series forecasting, experimentation, and other techniques
• Ability to draw insights and conclusions from data to inform model development and business decisions
• Desire to collaborate with data scientists, data analysts, and key business partners
• Intellectually curious, analytically thorough, hard-working, good work ethic and an on-point business intuition

• Experience developing scalable mathematical models and solving sophisticated quantitative problems that can be understood by non-mathematical colleagues
• Proven skills in selecting the right statistical tools given a data analysis problem
• Strong interpersonal skills, for both technical and non-technical audiences
• Ability to prioritize multiple tasks concurrently and in a timely manner
• Experience thinking strategically to interpret market and consumer information, preferably about a subscription service
• Familiarity with data platforms and applications such as Databricks, Jupyter, Snowflake, Airflow, Git Hub
• Familiarity with designing and analyzing A/B testing and other experiment types
• Some experience with distributed data technologies (Hive, Spark)

• Bachelor’s degree in Data Science, Mathematics, Statistics, Computer Science, or comparable field of study, and/or equivalent work experience.

• Master’s degree in Data Science, Mathematics, Statistics, Computer Science, or comparable field of study, and/or equivalent work experience.

The hiring range for this position in Santa Monica, CA is $93,400 to $125,200 per year based on a 40-hour work week. The amount of hours scheduled per week may vary based on business needs. 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.