Staff Data Scientist, Revenue

About the Role

The Revenue Data Science team plays a critical role in understanding revenue performance, modeling future outcomes, and providing a clear view of Mozilla's revenue outlook. This team's work supports planning, investment decisions, and executive discussions across a rapidly evolving product and market landscape. As part of this team, the Staff Data Scientist will work closely with Finance and senior leadership, contributing to strategic decision-making.

Mozilla's mission to make the internet better for people drives its work in diverse areas, including AI, social media, security, and more. With a focus on open-source software and a commitment to community-driven initiatives, Mozilla offers a unique environment for professionals who value openness, privacy, and innovation.

What You Will Do

• Own Mozilla's search revenue forecasting program end-to-end, including model development, scenario analysis, and executive-facing reporting.
• Develop and maintain forecasting models in Python, selecting appropriate approaches and validating results to ensure accuracy and reliability.
• Translate complex trends, assumptions, and trade-offs into clear narratives for Finance and senior leadership, including live VP-level discussions.
• Evaluate the impact of key drivers, uncertainties, and evolving conditions to inform planning and decision-making.
• Establish best practices for forecasting, validation, and reporting, and mentor other Data Scientists contributing to revenue-related work.
• Collaborate with cross-functional teams to integrate insights from various data sources and stakeholders.
• Stay updated on industry trends and advancements in data science and machine learning, applying this knowledge to improve forecasting models and methodologies.
• Contribute to the development of data visualizations and reports to effectively communicate insights to non-technical stakeholders.
• Participate in strategic planning sessions to provide data-driven insights that inform business decisions.

What We Are Looking For

• 8+ years of experience in data science, analytics, or applied quantitative roles, with demonstrated ownership of complex, business-critical analytical programs.
• Strong technical foundation, including advanced Python and SQL, with experience building, validating, and maintaining forecasting or decision-support models.
• Demonstrated ability to exercise sound judgment in ambiguous environments—balancing rigor with pragmatism to deliver directional, decision-ready insights when perfect precision is not possible.
• Proven ability to communicate complex technical concepts to non-technical stakeholders, including executive leadership.
• Experience with data visualization tools and techniques to effectively communicate insights.
• Strong collaborative mindset with the ability to work closely with cross-functional teams.
• Advanced degree in a quantitative field (e.g., Computer Science, Statistics, Mathematics) or equivalent experience.
• Experience with cloud-based data platforms and big data technologies.

Nice to Have

• Experience with machine learning algorithms and their application in forecasting and predictive analytics.
• Knowledge of web technologies and the ability to analyze web-related data.
• Familiarity with open-source software development and community engagement.
• Experience in a remote work setting, with the ability to manage time effectively and collaborate with distributed teams.
• Certification in data science or a related field.

Benefits and Perks

• Competitive compensation package.
• Comprehensive health insurance.
• Generous PTO and holiday policy.
• Remote work stipend to support your home office setup.
• Opportunities for professional development and growth within the company.
• Access to cutting-edge technologies and tools.
• Collaborative and dynamic work environment with a mission-driven team.
• Flexible working hours to accommodate different time zones and schedules.

• Ensure your portfolio includes examples of complex data analysis and forecasting models you've developed, highlighting your ability to communicate insights to both technical and non-technical stakeholders.
• Develop a strong understanding of Python and SQL, as these are core skills required for the role. Practice building and validating forecasting models using these tools.
• When applying, tailor your resume and cover letter to emphasize your experience in data science, especially in revenue forecasting and analysis.
• Prepare to discuss your approach to balancing technical rigor with practical business considerations during the interview process.
• Highlight any experience you have working with distributed teams or in a remote work setting, as this is a fully remote position.
• Be ready to provide specific examples of how you've handled ambiguous or complex data analysis tasks in the past, focusing on your problem-solving skills and judgment.
• Consider learning more about Mozilla's products and mission before the interview, to show your enthusiasm for the company and the role.