Senior Data Analyst

Optomi, in partnership with a leading Direct to Consumer Data & Analytics organization, is looking for a Sr. Data Analyst to join their Strategic Forecasting & Decision Analytics team.

The Sr. Data Analyst will apply analytical rigor to optimize strategic decisions based on decision and data science principles. This role focuses on QA, efficiency, and query optimization for products that streamline strategic decision support, content portfolio management, merchandising, acquisition & licensing, release strategy optimization, and churn & subscriber health. The ideal candidate thrives in a fast-paced environment, is a strong communicator, and is passionate about television and film.

• Joining a team that applies cutting-edge analytics to drive global business decisions
• Working on complex statistical models that predict future slate content engagement and subscriber lifetime value
• Opportunities to utilize creativity in solving open-ended problems
• Must be located in Santa Monica, CA;
  North Carolina;
  New York;
  San Francisco, CA

• STEM degree and relevant experience
• 5+ years of analytical and QA experience
• 5+ years of experience developing and productionalizing machine learning models
• 5+ years of experience querying cloud-hosted databases with SQL
• Expertise in statistical analysis and machine learning techniques (e.g., time-series forecasting, causal inference, regression, clustering)
• Outstanding data storytelling skills through verbal, written, and visual communication
• Familiarity with data visualization tools (Looker, Tableau, Jupyter Lab/Notebook)
• Experience with modern data pipeline tools such as dbt or Airflow
• Experience engineering and maintaining data solutions using Databricks, S3, and Spark

• Streamline complex statistical model products to predict future content engagement and subscriber lifetime value
• Apply advanced analytical engineering techniques focusing on QA, efficiency, and code optimization
• Support complex projects, work streams, and new initiatives, including scoping, managing resources, and adapting plans to operational challenges
• Effectively communicate actionable results through compelling data storytelling
• Design, build, and maintain scalable data pipelines
• Automate data workflows and operational processes using Python to improve reliability and enable faster delivery of insights