Principal GTM Operations Analyst

About the role

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 to a strong culture of technical rigor, peer review, and knowledge sharing within Sales Intelligence and the broader GTM Operations community

What We're Looking For

Experience

• ~8-12+ years in analytics, sales operations, data science, or strategy/consulting roles supporting B2B or SaaS go-to-market teams (or equivalent high-impact analytical experience)
• Demonstrated track record owning complex analytics projects end-to-end (from scoping through production deployment and stakeholder adoption), ideally in forecasting, segmentation/territory design, or account/deal scoring domains
• Track record of leading multi-quarter, cross-functional analytics programs and influencing executive decisions without direct authority
• Experience setting technical direction or standards for a team or a portfolio of production models
• Experience working directly with senior commercial stakeholders (e.g., Sales/GTM leaders) and turning analysis into concrete decisions and measurable business impact

Technical Skills

• Advanced SQL and strong Python (or equivalent) for data wrangling, feature engineering, and statistical / ML modeling
• Comfort working with large, messy datasets spanning CRM (Salesforce), product usage, and marketing/sales engagement tools
• Experience with at least one modern BI / analytics environment (e.g., Sigma, Looker, Tableau) and building self-serve, governed assets for business users
• Solid grounding in statistical thinking (sampling, backtesting, lift/impact measurement) and model validation practices
• Experimentation and causal inference (e.g., A/B and holdout design, difference-in-differences, regression discontinuity)
• Experience with forecasting and time-series models

Problem-Solving & Communication

• Ability to decompose ambiguous business questions into structured analytical plans, with clear assumptions, risks, and trade-offs
• Strong written and verbal communication: you can explain complex models and data decisions in simple, GTM-friendly language and build trust with non-technical stakeholders
• Bias toward action and ownership: you are comfortable making recommendations under uncertainty and iterating as new data arrives

Nice to Have

• Prior experience in Sales Operations / Revenue Operations or GTM Strategy at a high-growth SaaS company
• Experience with commercial applications of NLP / LLMs (e.g., call transcript analytics, opportunity notes analysis)
• Familiarity with MongoDB's ecosystem (Atlas, GTM motions, sales process) or similar modern cloud data platforms
• Experience contributing to cross-functional programs such as Customer 360, self-serve analytics initiatives, or GTM data/metrics standardization

Mongodb's base salary range for this role in the U.S. is

$84,000 - $165,000 USD