Summary
The Wikimedia Foundation is looking for a Data Science Manager to lead the Product Analytics team, reporting to the Senior Director, Research and Decision Science. In this role, you will lead a team of data scientists whose insights guide strategies and tactics aimed at achieving our vision: a world in which every single human being can freely share in the sum of all knowledge. Your team partners with product managers, designers, engineers, and colleagues across the Wikimedia movement to produce and share actionable and accessible data and insights to inform decision-making within the Foundation and in Wikimedia communities.
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.
Candidates must be located within the UTC+1 to UTC-8 time zones, available for critical meetings and synchronous work between 14:00 and 22:00 UTC, and able to travel for offsites and conferences (up to 4 times per year).
You are responsible for:
- Timely delivery of accurate quantitative data and insights to inform strategy, guide product decisions, and assess the impact of product development work – balancing the need to operate in a fast-changing environment with appropriate rigor.
- 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.
- 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.
- Continuous development and improvement of experimentation and measurement best practices, product health metrics, visualizations, and reports for easier interpretation and increased accessibility.
Skills and Experience:
- 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).
Qualities that are important to us:
- Ability to identify where data can have the most impact and clearly communicate findings and recommendations to partner teams
- Empathy towards and commitment to work with the Wikimedia affiliates and volunteer communities.
- Discretion and competence in handling sensitive or confidential data.
- Curiosity and critical thinking skills; a lifelong learner who sees situations through multiple lenses.
- A coach and mentor with high emotional intelligence: evidenced by humility, tact, compassion, high levels of integrity, and good listening skills.
- A facilitator with strong collaboration skills and an empowerment approach to open and transparent management.
- Commitment to the mission of the organization and our values and guiding principles.
- Self-motivated with an ability to navigate through ambiguity and complexity. The Wikimedia ecosystem is complex, resources are limited, and our guiding principles are ambitious. We want you to work to find solutions embracing these factors.
Additionally, we’d love it if you have:
- Exposure to, and interest in, ethical data management and privacy practices.
- Contributed to Wikimedia projects or have experience working in other open source projects.
- Experience with Superset, Growthbook, or other open-source testing, data visualization, or reporting tools.