Senior Manager, Product Analytics

About the Role:

• Hire, manage, and grow a team of analysts embedded across core product areas. Set the team’s analytical agenda, establish quality standards, and create an environment where analysts do their best work. Build the organizational capabilities across tooling, methodology, and craft that make the team a true force multiplier for product and engineering. 

• Build and maintain the authoritative measurement model for the in-app product experience: app launches, feature enrollment rates, journey analytics and notification performance. Ensure consistent metric definitions, data accuracy, and reliable reporting across teams, dashboards, and business reviews. 

• Partner with product and design to measure and optimize the end-to-end in-app customer experience, including onboarding flows, feature discoverability, enrollment funnels, and engagement patterns. Surface the behavioral signals that explain what’s driving adoption and what’s holding it back across key features including VPN, Dark Web Monitoring, Email and Text Scam Protection, Personal Data Cleanup, and Safe Browsing. 

• Measure the effectiveness of McAfee’s in-app notification strategy across iOS and Android. Track and interpret CTR, permission disable rates, journey entry rates, and downstream engagement. Diagnose underperforming notifications by distinguishing frequency fatigue, content relevance, and delivery timing issues, and collaborate with the Notifications Track and product teams to drive continuous improvement. 

• Build and maintain the analytics framework for McAfee’s directed journeys, from notification delivery through issue resolution. Define what “completion” means for each journey type, identify funnel drop-off, and surface actionable recommendations to improve journey start and resolution rates. Ensure telemetry models are robust enough to answer the questions that matter: did the customer resolve their issue? 

• Design, execute, and analyze A/B and multivariate tests across the in-app experience: onboarding, feature enrollment flows, notification content and frequency, and journey UX. Build an experimentation culture and framework that enables product teams to test confidently and interpret results rigorously. Bring deep expertise in hypothesis testing, confidence intervals, lift analysis, and quasi-experimental methods. 

• Partner with engineering and product to define, implement, and validate event instrumentation across the in-app analytics stack. Own the analytics team’s relationship with Data Engineering to ensure reliable, scalable data pipelines. Establish standards for event taxonomy, tagging, and telemetry model design that support both current reporting needs and future analytical flexibility. 

• Build and maintain dashboards that provide clear, real-time visibility into in-app performance, feature health, and customer journeys. Develop self-serve capabilities that reduce ad hoc burden and empower product managers to answer their own questions. Own the analytics narrative in business reviews and leadership forums, translating complex multi-signal analyses into concise recommendations that drive alignment and action. 

• Elevate the quality of measurement and decision-making across your cross-functional partners. Act as the resident expert on metric design, experimentation methodology, causal inference, and platform analytics best practices. Ensure the team’s outputs are held to a bar that leadership can act on with confidence. 

About You:

• 10 to 12 years of experience in product analytics, mobile analytics, or a related data-intensive role, ideally within a subscription, SaaS, or consumer technology business. 

• Demonstrated experience managing and growing a team of analysts. You know how to hire well, give clear feedback, develop careers, and build a team culture grounded in curiosity and high standards. 

• Hands-on experience measuring in-app user behavior across iOS and Android, including engagement funnels, feature adoption, notification performance, push CTR, and permission dynamics. Strong understanding of mobile telemetry, event tracking, and the analytical challenges that come with cross-platform measurement. 

• Demonstrated experience designing and analyzing A/B and multivariate tests. Solid statistical foundation including hypothesis testing, confidence intervals, lift analysis, and quasi-experimental methods such as difference-in-differences and regression discontinuity. 

• Expert proficiency in SQL and experience analyzing large-scale behavioral datasets. Proficient in Python for analysis and statistical work. Comfortable operating across high-volume, high-complexity data environments. 

• Hands-on experience working with engineers and product teams to define and validate mobile event tracking and in-app instrumentation. Experience with analytics tools such as Heap, Amplitude, Mixpanel, or similar, and BI platforms such as Looker, Tableau, or Power BI. 

• Track record of translating complex analytical findings into clear, executive-ready recommendations. Comfortable owning the analytics narrative in leadership forums and influencing product and engineering roadmaps through data. 

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