Marketing Data Science Lead

Job Description

Marketing Data Science Manager | Mozilla

The Tone:
This is a full-time role at Mozilla, located in World Wide Remote locations. Mozilla is a non-profit-backed technology company that has shaped the internet for the better over the last 25 years, known for pioneering brands like Firefox. With over 225 million monthly users, the company is focused on shaping the next 25 years of technology, reclaiming an internet built for people, not companies, and addressing diverse areas like AI, social media, and security. In this role, Marketing Data Science is essential for evaluating Marketing’s impact, developing clear strategies, translating broad goals into defined objectives, and identifying paths to success for Firefox’s continued growth.

The TL;DR
• Role: Full Time
• Type: Full-time
• Location: World Wide Remote

• Team: Marketing team; supports Firefox
• Mission: To evaluate Marketing’s impact and develop clear strategies to ensure Firefox’s growth, serving as thought leaders in translating broad goals into clearly defined objectives and identifying the path towards succeeding in them.
• Tech Stack: Google Analytics, advertising platforms, MMM, causal lift/synthetic control, saturation modeling, optimization, Bayesian approaches

What You’ll Actually Do
• Set Strategy: Set the strategy and roadmap for Marketing Data Science, prioritizing the highest-impact opportunities with key partners to drive Firefox’s growth.
• Measure Performance: Establish clear goals and measurement approaches for attribution, ROI, and campaign performance, delivering actionable insights that effectively improve marketing investment and overall outcomes.
• Develop Capabilities: Lead and develop the team’s core data science capabilities across performance marketing (budget optimization, causal lift, conversion testing), brand marketing (measurement planning, long-term and lower-funnel impact assessment), user insights (retention/LTV modeling, audience segmentation), and reporting/infrastructure (self-service dashboards, ad hoc/executive reporting, scalable data models, internal tools).
• Advance Methods: Bring a forward-looking perspective on emerging advertising trends, media innovation, and advanced marketing analytics methods to keep the team at the forefront.
• Adopt AI: Partner with Data Science leaders across domains to evaluate and responsibly adopt emerging AI tools and methodologies that can improve team workflows and overall impact.

The Must-Haves
• Background: Manager level, with core domain knowledge in marketing data science and its application to business growth.
• Experience: 6+ years of marketing data science experience, ideally gained at a media agency or in-house marketing organization, alongside proven experience leading, mentoring, and developing talent.
• Skills: Proficiency with marketing analytics tools including Google Analytics and advertising platforms; familiarity with modeling methods such as MMM, causal lift/synthetic control, saturation modeling, optimization, and Bayesian approaches; strong storytelling and communication skills for tailoring data-driven insights; strong stakeholder management; and the ability to prioritize multiple complex workstreams.