The Direct to Consumer Data & Analytics organization is seeking a Sr. Data Analyst to optimize strategic decisions based on decision and data science principles, focusing on Analytics Engineering, efficiency, and query optimization to grow products that streamline strategic decision support, content portfolio management, merchandising, acquisition & licensing, release strategy optimization, and churn & subscriber health.
Requirements
- 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.
- Familiarity with data exploration and data visualization tools such as Looker, Tableau, or JupyterLab/Notebook
- 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
- Bachelor’s degree in Data Science, Engineering, Mathematics, Statistics, Operations Research, Computer Science, Applied Economics or related quantitative field
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
- 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
- Support complex projects, workstreams, and new initiatives & capabilities
- Effectively communicate actionable results through compelling data storytelling across the organization
Other
- 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
- Demonstrated ability to work independently and apply creativity in solving open-ended problems
- Outstanding data storytelling skills through verbal, written, and visual communication
- Ability to explain how models are used and how algorithms behave to both technical and non-technical audiences
