Data Analyst - Observational Causal Inference

Job Posting Title:

Data Analyst - Observational Causal Inference

Req ID:

10129582

Job Description:

The Direct to Consumer Data & Analytics organization is seeking a Decision Analyst who will be an exceptional addition to our Strategic Forecasting & Decision Analytics team. As Decision Analyst, you will join our team that applies analytical rigor to optimize strategic decisions based on decision and data science principles. Projects include strategic decision support, content portfolio management, merchandising, acquisition & licensing, release strategy optimization, and churn & subscriber health. The right person for this role has exceptional analytical capabilities, thrives in a fast-paced environment, loves problem-solving, is a strong communicator, and is passionate about television and film. We are searching for someone who gains personal satisfaction from utilizing data to drive business decisions and is eager to learn. 

 

WHAT YOU’LL DO 

• Apply advanced analytics techniques (data mining, data visualization, statistical analysis, causal inference, regression, machine learning, time-series forecasting) to large-scale, high-dimensional data in order to inform global business decisions 

• Analyze customer behavior (e.g., genre preferences, viewing patterns) to identify unmet customer needs and untapped content opportunities 

• Use advanced causal inference methodologies to quantify engagement and overall impact of sharing title licenses with internal and external platforms 

• Predict content engagement to help guide acquisition decisions 

• Optimize our content launch and episode release strategy 

• Test merchandising strategies to optimize engagement and retention 

• Ideate and develop new metrics and KPIs, measuring content performance, engagement and churn for strategic decision-making 

• Support complex projects, workstreams, and new initiatives & capabilities. This includes scoping out the breadth & depth of a project, helping manage the time & resources available, adapting plans to meet evolving needs and operational challenges, and representing the product with business partners and executive leadership 

• Maintain relationships with stakeholders while understanding their needs and providing them with rapid and robust solutions to their requests 

• Provide ad-hoc analysis support for stakeholders to help move the business forward 

• Effectively communicate actionable results through compelling data storytelling across the organization 

WHAT TO BRING 

• Bachelor’s degree in Data Science, Mathematics, Statistics, Computer Science, Applied Economics, or a related field.

• 3+ years of experience in analytics, machine learning model development, and data analysis using Python and/or R.

• Proficient in querying cloud-hosted databases with SQL and engineering data solutions using technologies like Databricks, S3, and Spark.

• Applied expertise in observational causal inference methods (e.g., difference-in-difference, propensity score matching) for non-experimental settings.

• Skilled in statistical and machine learning techniques including time-series forecasting, regression, decision trees, and clustering.

• Strong data storytelling abilities across verbal, written, and visual formats.

• Effective communicator with both technical and non-technical audiences, capable of explaining model behavior and algorithmic decisions.

• Familiar with data exploration and visualization tools such as Looker, Tableau, and JupyterLab/Notebook.

• Demonstrated independence and creativity in solving open-ended problems.

NICE-TO-HAVES 

• Master of Science degree in Data Science, Mathematics, Statistics, Operations Research, Computer Science, Applied