Mongodb Manager, Customer Success Operations leads GTM model portfolio and roadmap, partnering with sales and analytics teams. Develops scalable analytics and machine learning models to improve sales forecasting and territory design.
Responsibilities
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
Qualification
~8-12+ years in analyticsTrack record of leading multi‐quarterTechnical SkillsComfort working with largeExperimentation and causal inference (eMongoDB is built for changeWith offices worldwide and over 67
Required
~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
Preferred
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 is built for change, empowering our customers and our people to innovate at the speed of the market. We have redefined the data platform for the AI era, enabling builders to create, transform, and disrupt industries with software. MongoDB’s unified data platform, the most widely available, globally distributed data platform on the market, helps organizations modernize legacy workloads, embrace innovation, and unleash AI. Our cloud-native platform, MongoDB Atlas, is the only globally distributed, multi-cloud data platform and is available across AWS, Google Cloud, and Microsoft Azure.
With offices worldwide and over 67,000 customers, including AI-native startups and approximately 75% of the Fortune 100, relying on MongoDB for their most important applications, we’re powering the next era of software.
Our compass at MongoDB is our Leadership Commitment, guiding how and why we make decisions, show up for each other, and win. It’s what makes us MongoDB.
To drive the personal growth and business impact of our employees, we’re committed to developing a supportive and enriching culture for everyone. From employee affinity groups, to fertility assistance and a generous parental leave policy, we value our employees’ wellbeing and want to support them along every step of their professional and personal journeys. Learn more about what it’s like to work at MongoDB, and help us make an impact on the world!
Manager, Customer Success Operations at Mongodb · LumiJobs
