Senior Data Analyst optimizing strategic decisions through analytics engineering. Leveraging advanced analytical techniques for data-driven insights in television and film.
Responsibilities
Use your indepth knowledge of code efficiency, optimization and refinement to help streamline our complex statistical model products that predict future slate content engagement and lifetime value of new and existing subscribers
Apply advanced analytical engineering techniques focusing on QA analysis, efficiency and code optimization and productionalization to large-scale, high-dimensional data models in order to inform global business decisions
Streamline and enhance 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 support the inform global business decisions
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
Effectively communicate actionable results through compelling data storytelling across the organization
Design, build, and maintain scalable data pipelines that transform raw data into reliable, analytics-ready datasets
Automate data workflows and operational processes using Python to improve reliability, reduce manual effort, and enable faster delivery of insights.
Requirements
Bachelor’s degree in Data Science, Engineering, Mathematics, Statistics, Operations Research, Computer Science, Applied Economics or related quantitative field
5+ years of analytical and QA experience
5+ years of experience developing and making efficient and productionalized machine learning models and performing data analysis with Python and/or R
5+ years of experience querying cloud-hosted databases with SQL
Experience with statistical analysis and machine learning techniques: time-series forecasting, causal inference, regression, decision trees, clustering, etc.
Demonstrated ability to work independently and apply creativity in solving open-ended problems
Outstanding data storytelling skills through verbal, written, and visual communication
Familiarity with data exploration and data visualization tools such as Looker, Tableau, or JupyterLab/Notebook
Ability to explain how models are used and how algorithms behave to both technical and non-technical audiences
Experience working with modern data pipeline and orchestration tools such as dbt, Airflow, or similar technologies
Experience engineering, deploying, and maintaining data solutions using technologies like Databricks, S3, and Spark
Benefits
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
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