The opportunity
The Central Sales Analytics team at MongoDB sits at the center of how we understand and improve the performance of our revenue engine. While this role is rooted in Sales Analytics, its scope is broader and spans key parts of the GTM organization.
What you'll do
Partner with Sales, Sales Operations, Strategy & Planning, FP&A,: Compensation, GTM Tech, and broader GTM stakeholders to identify high-value analytical opportunities and turn them into actionable insights
Lead deep-dive analyses across pipeline health, funnel conversion, seller: productivity, quota attainment, coverage and territory effectiveness, forecasting, and broader GTM performance trends
Translate ambiguous business questions into structured analyses, clear: recommendations, and scalable data solutions
Connect GTM outcomes with product and customer signals to identify growth: opportunities, improve prioritization, and deepen understanding of the customer journey
Partner selectively with Product and Technical teams to inform decisions that: sit at the intersection of commercial strategy, product behavior, and operational execution
Collaborate with GTM Tech, Atlas Core, and Emerging Products to combine: business context with technical and product signals in ways that improve insight generation and strategic alignment
What they're looking for
- + years of experience in Sales Analytics, GTM Analytics, Revenue Analytics,: Business Analytics, or a closely related field
- Strong fluency in both SQL and Python; both are core requirements for success in this role
- Proven ability to work with large, messy datasets and translate complex: analyses into clear business insights and recommendations
- Strong background supporting go-to-market, sales, revenue, customer, or: commercial organizations in a SaaS or high-growth technology environment
- Demonstrated ability to work across business and technical teams and: influence decisions through data, structured thinking, and clear communication
- Experience building scalable analytics assets such as data models,: dashboards, automated workflows, decision frameworks, or reusable insight products
- Ability to connect business questions to product usage, customer behavior,: and operational signals in a way that drives action
- Strong foundation in data modeling, metric design, data quality, and data governance principles
