Senior Data Scientist

To learn the Hiring Ranges for this position, please select your location from the Apply Now dropdown menu.

To learn more about our Hiring Range System, please click this link.

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 Senior Data Scientist, you are an inquisitive problem solver who is keen to practice full-stack data science, with experience ranging from crafting data extraction pipelines to finding patterns and anomalies in data. You have a strong curiosity and a desire to hone your technical skills further on a wide variety of real-world data. You believe that data science can lead to insights that can guide the future development of Firefox. You will apply your expertise in quantitative analysis, statistical modeling, and data visualization to see beyond the numbers and understand how our worldwide community experiences our products.

As a Senior Data Scientist on the GTM Data Science team, you will drive the analytical backbone of Mozilla’s revenue optimization and business development efforts. This role is ideal for a technically strong and commercially minded data scientist who thrives at the intersection of analytics, predictive modeling, and business strategy. You will own and deliver advanced forecasting models, help define and monitor business KPIs, and partner with stakeholders across Product, Marketing, and Finance to guide decision-making using data.

You will also support Mozilla’s mission to build a better, privacy-respecting internet by enabling efficient, data-driven go-to-market strategies across geographies and products.

What you’ll do:

• Design, own, and scale forecasting models that inform revenue planning, demand estimation, and growth strategies (e.g., product revenue and key revenue drivers), with a focus on automation and long-term reusability.
• Build robust, well-documented data sets and forecasting pipelines that support both day-to-day operations and deeper strategic analysis across teams.
• Develop clear, intuitive dashboards and tools in Looker to help teams explore data, track performance, and make fast, informed decisions.
• Collaborate with GTM teams to build ROI-focused frameworks that drive insights across campaigns, markets, and customer segments.
• Lead deep-dive analyses into user behavior, engagement, and monetization funnels to uncover opportunities and improve outcomes.
• Break down complex business questions into clear analytical approaches, and communicate findings and trade-offs with clarity to cross-functional stakeholders.
• Promote strong data quality and lead efforts to standardize key metrics across business functions.
• Champion a data-driven culture by contributing to best practices, encouraging experimentation, and fostering continuous learning across the data science community at Mozilla.

What you’ll bring:

• Master’s or PhD in Data Science, Statistics, Computer Science, or a related field
• 2+ years of professional experience doing quantitative analysis, particularly in an Internet-focused, consumer-focused organization
• Background in applied statistical modeling on large experimental or observational data sets
• Experience extracting data from a variety of sources (solid understanding of SQL is required)
• Proven ability to build forecasting, causal inference, and time series models (ARIMA, Prophet, Bayesian approaches, etc.).
• Profi