Senior Sales Operations Analyst

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 Senior Analyst on the Applied Science team, you will own high‑impact analytical workstreams end‑to‑end: from problem framing with senior GTM stakeholders, to data engineering and model design, through to productionalized workflows, dashboards, and executive‑ready narratives that drive concrete changes in the field. This role is based in Dublin, Ireland and supports a global stakeholder set across regions and GTM functions. We are looking to speak to candidates who are based in Dublin for our hybrid working model. What You’ll Do - 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 - Contribute to 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. - 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 - Help shape and exploit new GTM data sources such as call transcript modeling, workload inference, and account intelligence to unlock novel scoring and routing use cases. - Partner with Central Analytics and GTM Tech on best practices for testing, monitoring, documentation, and change management for GTM models and analytics products. - Coach, document, and uplevel the org - 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 - ~4–7+ 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. - 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. 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

Experience: ~4–7+ 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. 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. 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: ability to explain complex models and drive decisions.