Staff Data Scientist - Operations

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Why Mozilla?

Mozilla Corporation is the non-profit-backed technology company that has shaped the internet for the better over the last 25 years. We make groundbreaking brands like Firefox, the privacy-minded web browser. Now, with more than 225 million people around the world using our products each month, we’re shaping the next 25 years of technology and helping to reclaim an internet built for people, not companies. Our work focuses on diverse areas including AI, social media, security and more. And we’re doing this while never losing our focus on our core mission – to make the internet better for people.

The Mozilla Corporation is wholly owned by the non-profit 501(c) Mozilla Foundation. This means we aren’t beholden to any shareholders — only to our mission. Along with thousands of volunteer contributors and collaborators all over the world, Mozillians design, build and distribute open-source software that enables people to enjoy the internet on their terms.

About this team and role:

As a Staff Data Scientist supporting Global Operations, you will be a strategic partner in improving Mozilla’s operational efficiency, effectiveness, and scale. You are a hands-on builder who brings a strong analytical toolkit, fluency in AI technologies, and a deep appreciation for how complex operational systems work. You will lead foundational reporting efforts, automate critical workflows, and identify opportunities to reduce cost and improve performance across Customer Experience, Trust & Safety, and Ad Operations.

You thrive in environments where productivity, pragmatism, and impact matter more than perfection. You think like an operator and build like an engineer. You know that good metrics and fast insights are the foundation for running great teams, and you want to make that a reality at Mozilla.

What you’ll do:

• Lead the development of foundational reporting and metrics infrastructure for Global Operations, enabling timely, trusted visibility across the various Ops orgs. 
• Design and scale measurement frameworks that surface operational trends and performance drivers.
• Apply AI and automation tools (e.g. LLMs, GPT-based summarization, anomaly detection, task triage) to eliminate manual workstreams and improve productivity.
• Prototype and implement automation use cases that drive operational efficiency and compliance, while identifying similar opportunities for cost savings across the organization
• Define and implement core operational metrics that reflect efficiency, effectiveness, and service quality, enabling measurement at scale and continuous process improvement.
• Partner with operations, and product teams to define measurement needs, identify gaps, and implement tracking.
• Standardize operational metrics and dashboards in Looker, ensuring self-serve access and consistency across the organization.
• Drive root cause analysis and opportunity sizing to surface the highest-value areas for investment or process improvement.

What you’ll bring:

• BS or MS in Data Science, Statistics, Computer Science, or a related field
• 5+ years of experience in data science or analytics, with demonstrated work on operations-focused projects.
• Hands-on experience with AI tooling and prototyping, particularly in service of process automation (LLMs, APIs, NLP, anomaly detection).
• Familiarity with operational domains such as Customer Experience (CX), Trust & Safety (T&S), or Ad Ops; ability to understand metrics like handle time, task pacing, or SLA completion without needing deep onboarding.
• Strong proficiency in SQL, and experience building data pipelines and dashboards using tools like Looker.
• Proficiency in Python or R for modeling, prototyping, and automation.
• Experience with metric standardization, KPI frameworks, and experimentation in operational settings.
• Ability to work cross-functionally, communicate with clarity, and prioritize speed over perfection when needed.
• Deep sense of ownership, curiosity, and urgency in solving problems that improve organizational productivity.
• A global, privacy-respecting perspecti