Senior Data Scientist - GTM Data
PandaDoc - Remote (USA)
Posted May 11, 2026
Benefits
- Parental leave
- Not verified
- Non-birth-parent leave
- Not verified
- Family-building benefits
-
- Fertility benefits: Not verified
- Adoption assistance: Not verified
- Surrogacy assistance: Not verified
- Mental health support
- Not verified
- Relocation assistance
- Not verified
- Childcare support
- Not verified
- Learning budget
- Not verified
- Verification
- Not verified
- Salary
- $165K-$185K From the posting source checked Jun 20, 2026
- 401(k) match
- Not verified
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Market context
- U.S. role benchmark (BLS OEWS)
- $111,944 U.S. median for this role
- Projected growth (BLS Employment Projections)
- +13.7% - Much faster than average
56% above the BLS role benchmark for data and ml aggregate.
Matched to SOC 15-1252 - Data and ML aggregate by role bucket.
Source: U.S. Bureau of Labor Statistics, OEWS, May 2024 and Employment Projections, 2024-2034.
Role
Schedule
- Shift type
- Not verified
- Weekend work
- Not verified
Application
- Cover letter
- Not verified
- Assessment
- Not verified
- Deadline
- Not stated
Where they hire
State eligibility is not yet verified.
About this role
Senior Data Scientist - GTM Data Remote (USA) The Opportunity As a Senior GTM Data Scientist at PandaDoc, you will be a critical analytical partner to our Go-To-Market (GTM) teams. You will embed yourself in our GTM data to uncover insights and drive actionable recommendations across Sales, Marketing, and Customer Success. The core of this role is to design, build, and maintain predictive machine learning models that optimize customer acquisition, revenue attribution, and retention efforts. You will apply analytical rigor and methodologies like experimentation and causal inference to provide GTM leadership with a reliable understanding of business efficiency and impact. You will report to the Director of GTM Data and act as a reliable thought partner to Marketing, Sales, Customer Success, and Finance. What You'll Do Predictive Modeling & GTM Strategy - Model Development: Design, build, and deploy foundational GTM models, including Customer Lifetime Value (LTV) forecasting, Marketing and Sales Attribution, and Propensity models (e.g., propensity to convert, churn, or expand). - GTM Experimentation: Partner with GTM teams to design and analyze controlled experiments across various channels, including website A/B testing, pricing experiments, and marketing campaign effectiveness. You will use methodologies such as AB, multivariate, Bayesian, and Causal Inference. - Deep Dive Analysis: Execute proactive, complex analytical deep dives to discover latent user behavior and root causes of changes in GTM metrics, translating findings into actionable recommendations. - Marketing Mix Modeling (MMM): Support the interpretation of MMM results to help maximize marketing ROI and assess the feasibility of future in-house
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