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Key skills in this ad
Skills and tools
MongoDB
Machine learning
SQL
Python
AWS
Google Cloud
Azure
Experience
8-12+ years
Picked out automatically from the employer's ad. Read the full description before applying.
About this role
GTM Operations & Strategy at MongoDB is a global team of builders and innovators focused on unleashing ’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.
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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
About MongoDB
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,](https://www.mongodb.com/company) 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](https://www.mongodb.com/company/blog/culture/employee-benefits-that-make-a-difference-at-mongodb), 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](https://www.mongodb.com/blog/channel/culture), and help us make an impact on the world!
MongoDB is committed to providing any necessary accommodations for individuals with disabilities within our application and interview process. To request an accommodation due to a disability, please inform your recruiter.
MongoDB, Inc. provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type and makes all hiring decisions without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws.
Req ID: 2273430764
MongoDB’s base salary range for this role is posted below. Compensation at the time of offer is unique to each candidate and based on a variety of factors such as skill set, experience, qualifications, and work location. Salary is one part of MongoDB’s total compensation and benefits package. Other benefits for eligible employees may include: equity, participation in the employee stock purchase program, flexible paid time off, 20 weeks fully-paid gender-neutral parental leave, fertility and adoption assistance, 401(k) plan, mental health counseling, access to transgender-inclusive health insurance coverage, and health benefits offerings. Please note, the base salary range listed below and the benefits in this paragraph are only applicable to U.S.-based candidates.
MongoDB’s base salary range for this role in the U.S. is:
$84,000—$165,000 USD
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