Principal GTM Operations Analyst

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GTM Operations & Strategy at MongoDB is a global team of builders and innovators focused on unleashing MongoDB’s sales greatness by pairing world‑class analytics with scalable operations. Within GTM Operations, the GTM Intelligence - Applied Science team turns complex GTM data into tools, models, and insights that help our sales organization make better, faster decisions across our people, segmentation, territory design, forecasting, and account prioritization. As a Principal Analyst on the Applied Science team, you will set the technical direction for our GTM model portfolio and personally lead our highest‑stakes programs, from framing problems with SVP‑level stakeholders, through data engineering and model design, to productionalized workflows, dashboards, and executive‑ready narratives that change how the field operates. This role will be based remotely in the United States, and supports a global stakeholder set across regions and GTM functions. What You’ll Do Own the model portfolio and roadmap for one or more domains Set the multi‑quarter roadmap for a given GTM model portfolio domain, deciding what to build, retire, or invest in based on measured business impact Act as the senior analytical thought partner to GTM leadership, shaping which questions the team takes on, not just how it answers them Translate GTM questions into analytical projects Partner with GTM Ops, Sales Strategy & Planning, Sales Leadership, and Central Analytics to scope problems, define success criteria, and prioritize work across areas like segmentation, territory design, account prioritization, and pipeline/forecast health Structure ambiguous questions into hypotheses, analytical plans, and clear recommendations for senior stakeholders (SVPs, RVPs, functional leaders) Design and build scalable analytics & models Develop and maintain statistical and machine learning models (e.g., NARR prediction, deal qualification, account momentum, workload identification) that inform forecast expectations, territory assignments, and deal prioritization Engineer robust data pipelines and features (SQL/Python) on top of our GTM data stack (Salesforce, product usage, call transcripts, marketing signals, etc.) in partnership with data and platform teams Own core GTM analytics assets Lead flagship programs such as Forecasting 3.0 / Atlas Forecasting Calculator, Customer 360 Revamp, GTM Metrics 3.0, and territory optimization initiatives, ensuring they are statistically sound, explainable, and operationally durable Build and govern self‑serve analytics assets (e.g., Sigma workbooks, curated datasets) that allow GTM stakeholders to answer their own questions safely and consistently Measure and prove impact Design experiments, holdouts, and causal analyses that quantify the revenue and efficiency impact of our models and GTM investments, and make that evidence the basis for investment decisions Turn analysis into decisions and change Deliver concise, executive‑ready narratives (memos, scorecards, and QBR/MBR content) that highlight trade‑offs and explicit recommendations, not just data and charts Run stakeholder working sessions to align on scenarios, validate model outcomes, and embed recommendations into operating rhythms (e.g., segmentation reviews, annual planning, forecast calls) Advance our GTM data & AI foundations Define how we use new GTM data sources such as call transcript modeling, workload inference, and account intelligence to unlock novel scoring and routing use cases Set the standards for testing, monitoring, documentation, and change management of GTM models and analytics products, in partnership with Central Analytics and GTM Tech Multiply the team Mentor analysts and data scientists, review their technical work, and raise the bar for rigor across our teams Create clear documentation, playbooks, and training to help other analysts and GTM stakeholders understand and safely use the models, tools, and datasets you own Contribute t

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