# Senior GTM Data Scientist

**Company:** [PandaDoc](https://hotfix.jobs/companies/pandadoc)
**Location:** Remote
**Role:** Data Science
**Salary:** Up to $185k/yr
**Experience:** 4+ years
**Skills:** Python, R, SQL, scikit-learn, pandas, NumPy, Machine Learning, Causal Inference, A/B Testing, dbt, Airflow, Databricks, Snowflake, Marketing Mix Modeling
**Posted:** 2026-07-07

> Senior GTM Data Scientist partnering with Sales, Marketing, and Customer Success teams. Design and deploy predictive ML models (LTV, attribution, propensity), run experiments with causal inference, and translate insights into actionable GTM strategies. Requires 4+ years in applied data science with strong Python/SQL and experimentation skills.

## Job Description

## What You'll Do

### Predictive Modeling & GTM Strategy
- 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).
- Partner with GTM teams to design and analyze controlled experiments across channels including website A/B testing, pricing experiments, and marketing campaign effectiveness using methodologies such as AB, multivariate, Bayesian, and Causal Inference.
- Execute proactive, complex analytical deep dives to discover latent user behavior and root causes of changes in GTM metrics, translating findings into actionable recommendations.
- Support the interpretation of Marketing Mix Modeling (MMM) results to maximize marketing ROI and assess feasibility of future in-house modeling.

### Measurement & Technical Rigor
- Define, instrument, and govern a unified KPI framework that maps GTM activities (e.g., CAC, Funnel conversion, Retention) to high-level business outcomes.
- Translate complex statistical findings and model outputs into compelling business narratives for cross-functional partners.
- Work closely with Data Engineering to ensure data quality, reliable instrumentation, and development of reusable predictive assets like model feature stores.
- Provide technical guidance to peers and stakeholders on best practices for data exploration, ML modeling, and causal methodologies.

## About You

### Qualifications
- 4+ years of professional experience in an applied data science, economics, or GTM analytics role with a proven track record of leveraging predictive modeling and experimentation to drive measurable business impact.
- B.A. or B.S. in Mathematics, Statistics, Economics, Computer Science, or a related quantitative discipline. Master’s degree preferred.

### Technical Expertise
- Demonstrated experience building and validating production-ready models for business applications (LTV, Attribution, Propensity).
- Practical application of Causal Inference methods such as Quasi-Experimentation, Matching Methods (PSM), and Difference-in-Differences.
- Proficiency in statistical methodologies for A/B testing including sample size calculations, sequential testing, and variance reduction techniques.
- Advanced proficiency in Python or R (Scikit-Learn, pandas, numpy) and expert-level SQL.
- Experience with tools like dbt, Airflow, Databricks, or Snowflake is a strong plus.

### Key Attributes
- Strong data storytelling skills to influence cross-functional partners and drive consensus in ambiguous environments.
- Ability to translate complex business questions into clear analytical frameworks while managing multiple priorities.
- Experience in a SaaS domain supporting Sales, Marketing, or Customer Success is highly preferred. Experience building LTV, attribution, and propensity models strongly preferred.

## Benefits
- The annual OTE for this role is up to $185k.
- Remote-first approach.

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