Senior Manager, Data Science & Analytics (Revenue & Growth), Yahoo Mail

Job Description

Yahoo Mail is the ultimate consumer inbox with hundreds of millions of users. It’s the best way to access your email and stay organized from a computer, phone or tablet. With its beautiful design and lightning fast speed, Yahoo Mail makes reading, organizing, and sending emails easier than ever.

About The Organization Yahoo, with a strong foundation of 900 million monthly users, is in the midst of a renaissance—backed by substantial investment to drive meaningful, long-term growth, led by great products. Are you up for the challenge of writing the story of one of the biggest consumer product success stories in history? This won’t be easy, but if you’re motivated by huge opportunities, backed by an organization ready to invest in bold initiatives, and can’t wait to start building, Yahoo is the place for you. Yahoo is composed of organizations, each led by a GM, driving key product lines.

This role sits within the Yahoo Mail group, home to one of the largest consumer email platforms in the world, serving over 200 million monthly users. You’ll be part of the team shaping the next phase of growth—building smarter, data-driven products and experiences that deepen engagement and expand revenue.

Position Overview Reporting to the Senior Director, Strategy & Analytics, the Senior Manager, Data Science & Analytics (Revenue & Growth) will lead the analytics and experimentation strategy that powers Yahoo Mail’s growth and monetization engine. You will oversee a team of data scientists supporting Ads, Commerce, Subscriptions, and User Growth squads. This is a highly visible, impact-oriented role for a technically strong, hands-on leader who thrives at the intersection of product, data, and business.

You’ll operate as a player-coach, guiding your team strategically while remaining close to the data. Expect to spend roughly 20% of your time coding, diving deep into complex analyses, validating models, and shaping the technical standards for the broader analytics organization. Responsibilities Revenue & Growth Analytics Leadership Own the analytics roadmap for Yahoo Mail’s revenue and growth squads, driving clarity around key performance metrics and success criteria.

Partner with Product, Finance, and Marketing to quantify opportunities, evaluate trade-offs, and connect product outcomes to business results. Develop models and frameworks that quantify ROI, forecast growth, and identify levers to accelerate performance across Ads, Commerce, and Subscription products.

Experimentation & Advanced Analytics Design, implement, and evolve a rigorous experimentation framework across monetization and growth initiatives. Be hands-on in Python and SQL—diving deep into data to validate hypotheses, uncover drivers of performance, and ensure statistical integrity of experiments. Develop scalable pipelines and reusable analytical tools that enable faster test iteration and decision-making across teams.

Cross-Functional Partnership & Stakeholder Management Work closely with Finance to align product metrics with financial impact—bridging the gap between user engagement, monetization, and P&L outcomes. Serve as a trusted thought partner to Product and Engineering leaders, translating data insights into strategic product direction. Communicate insights clearly and persuasively to senior leadership, turning analysis into actionable business narratives.

Team Leadership & Development Lead, mentor, and develop a team of five analysts—cultivating technical depth, business acumen, and ownership. Operate as a player-coach: set direction, unblock execution, and jump in hands-on when necessary. Foster a culture of curiosity, rigor, and scrappiness—driving high output with a lean, high-performing team.

Qualifications Experience: 8+ years in data science, analytics, or product analytics, with 3+ years of people management. Technical Expertise: Advanced proficiency in Python and SQL; strong applied statistics and experimentation design skills. Deep understanding of A/B testing methodologies, causal inference, and metric design.

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