In A Nutshell
As the Data Science Manager for Product Analytics, you will manage a team of data scientists who help product development teams use quantitative data and insights to understand our audiences, inform strategy, guide product decisions, and assess the impact of new features. You will be accountable for the work your team delivers, and you will ensure timely delivery, data accuracy, and consistent reporting by creating shared data processes and procedures. And you will support the design of data products and tools that make critical data more accessible to stakeholders and decision makers.
Responsibilities
- Informing strategy, guiding product decisions, and assessing the impact of product development work through your team’s timely delivery of accurate quantitative data and insights – balancing the need to operate in a fast-changing environment with appropriate rigor.
- Proactively making recommendations on product direction and data strategy, surfacing insights and interpreting results.
- People management for a team of roughly seven data scientists and nurturing a strongly collaborative and inclusive culture of trust, excellence, and empowerment.
- Mentoring team members on critical thinking, data-informed storytelling, technical skillset, and stakeholder partnership.
- Continuous development and improvement of experimentation and measurement best practices, product health metrics, visualizations, and reports for easier interpretation and increased accessibility.
- Partnering with the Experiment Platform & Data Engineering teams to build and maintain data products that make data and insights accessible.
- Collaborating with product teams – especially product managers – and colleagues in the Research & Decision Science group to cultivate a practice of data-informed product development and decision making.
Skillset
- Deep experience with experimental design and statistics, applied to internet-scale audience or user experience data.
- Experience collaborating with product development teams in a fast-paced environment to test, analyze, and evaluate user-facing features.
- Prior experience as a people manager.
- Demonstrated commitment to equity, inclusion, and diversity.
- Experience with large-scale data processing & storage tools (we use Hadoop, Hive, Presto, and Spark).
