Hybrid Data Analyst, Observational Causal Inference

Posted last month

Apply now

About the role

  • Apply advanced analytics techniques (data mining, data visualization, statistical analysis, causal inference, regression, machine learning, time-series forecasting) to large-scale, high-dimensional data 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 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, including scoping projects, managing time & resources, and representing the product with business partners and executive leadership
  • Maintain relationships with stakeholders and provide rapid, robust solutions and ad-hoc analysis support
  • Effectively communicate actionable results through compelling data storytelling across the organization

Requirements

  • 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 related field; a passion for media and entertainment

Benefits

  • Primarily On-Site / Occasionally from Home
  • A bonus and/or long-term incentive units may be provided as part of the compensation package
  • Full range of medical, financial, and/or other benefits (dependent on the level and position offered)

Job title

Data Analyst, Observational Causal Inference

Job type

Experience level

Mid levelSenior

Salary

$95,300 - $127,800 per year

Degree requirement

Bachelor's Degree

Location requirements

Report this job

See something inaccurate? Let us know and we'll update the listing.

Report job