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Marketing Data Science Manager
Mozilla
Contract type
Ongoing
Work mode
100% remote
Experience
Senior · 6+ years
Job description
Key details
- Set the strategy and roadmap for Marketing Data Science, prioritizing the highest-impact opportunities with key partners
- Establish goals and measurement approaches for attribution, ROI, and campaign performance; deliver insights that improve marketing investment and outcomes
- Lead and develop the team's core capabilities across performance marketing (budget optimization, causal lift measurement, conversion-signal testing), brand marketing (measurement planning and assessment of long-term and lower-funnel impact), user insights (retention/LTV modeling and audience segmentation), and reporting and infrastructure (self-service dashboards, ad hoc and executive reporting, scalable data models and internal tools)
- Bring a forward-looking perspective on advertising, media innovation, and marketing analytics methods
- Partner with Data Science leaders to evaluate and responsibly adopt emerging AI tools that improve team workflows and impact
- Company mission
- Mozilla exists to build the Internet as a public resource accessible to all because we believe that open and free is better than closed and controlled
Primary stack
Core technologies
Python (Programming Language)
Benefits
- Generous performance-based bonus plans to all eligible employees
- Rich medical, dental, and vision coverage
- Generous retirement contributions with 100% immediate vesting
- Quarterly all-company wellness days
- Country specific holidays plus a day off for your birthday
- One-time home office stipend
- Annual professional development budget
- Quarterly well-being stipend
- Considerable paid parental leave
- Employee referral bonus program
- Other benefits (life/AD&D, disability, EAP, etc. - varies by country)
Requirements & details
- 6+ years of marketing data science experience, ideally at a media agency or in-house marketing organization
- Proficiency with marketing analytics tools, including Google Analytics and advertising platforms, and familiarity with modeling methods such as MMM, causal lift/synthetic control, saturation modeling, optimization, and Bayesian approaches
- Proven experience leading, mentoring, and developing talent, with strong stakeholder management and the ability to prioritize multiple complex workstreams
- Strong storytelling and communication skills, with the ability to tailor data-driven insights and recommendations to different audiences
- Google Analytics, Python (Programming Language)
- Python (Programming Language)