Apple Inc. is looking to lead statistical analysis of performance of Sports and Video content using viewership, subscription, and event-based clickstream data to derive actionable insights and trigger business actions.
Requirements
- Performing statistical analysis using Python.
- Manipulating data with packages like Pandas, performing various statistical analyses such as descriptive and inferential analysis in order to learn about user behavior and its impact on the business.
- Querying and managing databases using SQL.
- Using SQL to access, explore, manipulate, and aggregate data.
- Evaluating feature performance with A/B Testing or causal inference.
- Building models using Scikit-learn and other Machine Learning Packages like SciPy, Prophet, and stats models.
- Managing pipelines for big data jobs and analysis using Spark and Hadoop.
Responsibilities
- Lead statistical analysis of performance of Sports and Video content using viewership, subscription, and event-based clickstream data.
- Analyze new feature usage to alter the product roadmap for specific features.
- Use statistical techniques such as causal inference, supervised learning methods including classification and forecasting (including autoregressive), and clustering to derive actionable insights and trigger business actions, including a predictive model to forecast game performance that is used to model modifications to the schedule, as well as a schedule optimizer for another league’s games that decides our schedule.
- Implement models and statistical analyses into production using Spark and Airflow.
- Work with Engineering partners to define logic for pipelines for official reporting for key business metrics both internally and for use by external partners, including royalty reporting, helping to define the pipeline logic from raw client events through sessionization and aggregation.
- Codify downstream or custom metrics, handle engineering pipelines using Spark and Airflow to ensure that key KPIs land in business tracking dashboards on time.
- Analyze the impact of new content and new product features based on metrics including subscription conversion, feature usage, and deepening viewership, and design experiments where appropriate to measure impact and guide future direction of the content and product roadmaps.
Other
- 40 hours/week.
- Distilling complex findings into digestible learnings for stakeholders.
- Working with Engineering to define data collection design and requirements.
- Experience with data architecture and infrastructure, and defining requirements of how best to structure the data to be usable.
- Base pay range for this role is between $163,300 - $245,800/yr
