About this team and role:
The Firefox Data Science team partners with Product and Engineering to grow usage of our flagship product: Firefox, the privacy-minded web browser. Our work informs prioritization, investment decisions, and the long-term growth strategy across Firefox.
This Staff Data Scientist will own the analytical strategy for a major product area: identifying the right questions, defining how success is measured, and driving decisions that shape Firefox’s growth trajectory. You will be a strategic partner to product and engineering leadership: framing problems, designing measurement approaches, and translating data into clear recommendations that influence roadmap and resource allocation. You will also raise the analytical bar across the team by establishing frameworks, mentoring other data scientists, and setting standards for how we measure and learn. This role requires the judgment to know which problems matter most, the technical depth to solve them rigorously, and the influence to ensure the work drives action.
What you’ll do:
- Own the analytical strategy for a product area: identifying the highest-leverage questions, defining the measurement framework, and ensuring data-driven decisions
- Serve as a strategic partner to product and engineering leadership, translating ambiguous business problems into analytical approaches and clear, actionable recommendations
- Define north-star metrics and measurement strategies to set goals, evaluate progress, and make trade-offs
- Design and oversee experiments and causal analyses, ensuring methodological rigor and that results drive real product decisions
- Develop and maintain a deep understanding of user growth dynamics: how acquisition, activation, and retention interact to drive growth, and use that understanding to diagnose metric movements, explain trends to leadership, and anticipate emerging risks or opportunities
- Contribute and own areas of the team’s forecasting and growth modeling efforts, helping translate statistical models into actionable growth strategies
- Mentor and elevate other data scientists through code review, methodology guidance, and establishing reusable analytical frameworks
- Represent data science in cross-functional forums, making the case for what the data shows even when it challenges prevailing assumptions
- Drive alignment across data science, data engineering, and product on shared priorities like data quality, metric definitions, and instrumentation
What you’ll bring:
- 8+ years of experience in data science, analytics, or applied quantitative analysis, with a track record of shaping product strategy through data
- Demonstrated ability to lead complex, cross-functional analytical initiatives from problem framing through stakeholder alignment to decision
- Deep expertise in experimentation (A/B testing) and causal inference, with strong judgment about when each method applies and what conclusions they support
- Advanced proficiency in SQL and Python for analysis, modeling, and validation
- Experience defining and owning product metrics that teams actually use to make decisions
- Strong opinions, loosely held: you can take a position on what the data says, advocate for it clearly, and update when the evidence changes
- Track record of mentoring or technically leading other data scientists