LI
LiteraData Analyst
Data Analyst within Revenue Operations designing scalable reporting and data solutions. Leveraging Power BI and SQL to support actionable insights for sales, marketing, and customer success teams.
TC
Hybrid Data Analyst – Observational Causal Inference
Posted 4 weeks ago
About the role
- Apply advanced analytics techniques to large-scale, high-dimensional data in order to inform global business decisions
- Analyze customer behavior to identify unmet customer needs and untapped content opportunities
- Use advanced causal inference methodologies to quantify engagement and overall impact of sharing title licenses
- 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.
- Maintain relationships with stakeholders while understanding their needs
- Provide ad-hoc analysis support for stakeholders to help move the business forward
- 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.
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 dependent on the level and position offered
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