PandaDoc · 3 hours ago
Staff GTM Data Scientist
United States
Full-time
Remote
Senior Level, Lead/Staff
6+ years expPandaDoc is seeking a Staff Data Scientist to serve as a senior analytical leader focused on driving a data-driven culture within the organization. The role involves leading experimentation efforts, conducting complex analyses, and providing strategic insights to influence business decisions.
Contact ManagementDocument ManagementE-SignatureSaaSSales AutomationSoftware
Responsibilities
Lead the Experimentation Roadmap: Define, champion, and execute a strategic roadmap for measuring impact across PandaDoc, focusing on high-leverage business questions related to customer workflows, churn risk, and long-term value (LTV)
Advanced Experiment Design: Design, implement, and rigorously analyze complex A/B tests, multivariate experiments, and adaptive experimentation methods, including the application of Bayesian experimentation, to assess the effectiveness of proposed product changes and business levers
Causal Inference Beyond A/B: Apply advanced causal inference techniques (e.g., difference-in-differences, synthetic control, propensity score matching, and instrumental variables) to scenarios where randomized controlled trials (RCTs) are infeasible
Deep Dive Analysis: Conduct complex, proactive, and exploratory analysis to discover latent user behavior, emerging trends, and root causes of changes in key metrics, translating these findings into actionable product and business insights
Develop Measurement Frameworks: Define, instrument, and govern a unified Key Performance Indicator (KPI) framework that maps low-level product health metrics to high-level business outcomes, ensuring consistent and scalable measurement across the organization
Scaling Data Science: Partner with Data Engineering to design and build scalable, self-serve experimentation tooling and reusable analytical assets and frameworks (e.g., causal machine learning models) that empower other analysts and data consumers
Strategic Influence: Act as a strategic thinker by translating complex statistical findings into clear, compelling, and actionable business narratives for cross-functional partners and senior leadership (VP/C-suite), driving strategic decisions and investment priorities
Mentorship and Training: Serve as a technical subject matter expert, training and mentoring junior and mid-level data scientists on best practices in statistical rigor, experimental design, and causal modeling
Qualification
Required
6+ years of professional experience in an applied data science, economics, or product analytics role, with a proven track record of leveraging experimentation and causal inference methods to drive significant business impact
B.A. or B.S. in Mathematics, Statistics, Economics, Computer Science, or a related quantitative discipline
Demonstrated expertise in applying a wide range of Causal Inference methods, e.g. Quasi-Experimentation, Matching Methods (PSM), Difference-in-Differences, and/or Instrumental Variables
Expertise in advanced statistical methodologies for A/B testing, including sample size calculations, sequential testing, dealing with interference/network effects, variance reduction techniques (e.g., CUPED), etc
Mastery of advanced statistical modeling, time-series analysis, and quantitative methods necessary to perform thorough exploratory data analysis, produce timely insights, and provide actionable recommendations
Advanced proficiency in Python or R for statistical modeling, with experience using relevant data science packages (e.g., SciKit-Learn, numpy, pandas)
Expert-level proficiency in SQL and experience working with established data warehouses (e.g., Snowflake, Postgres)
Experience with data transformation and workflow management tools such as dbt, Airflow, or Databricks is a strong plus
Possesses exceptional communication, presentation, and data storytelling skills with a consistent record of influencing cross-functional partners and leadership at all levels, particularly in navigating and driving consensus in unstructured or ambiguous environments
Proven ability to drive organizational change management in environments where experimentation and data-driven decision-making are not yet widely adopted
Ability to navigate significant ambiguity, translate complex business questions into clear analytical frameworks, and manage multiple competing priorities in a fast-paced environment
Preferred
A Master's degree in a quantitative field (e.g., Statistics, Data Science, Econometrics, Operations Research)
Experience in a SaaS domain and a strong focus on Product Data Science are strongly preferred
Benefits
Tremendous career growth opportunities
A competitive salary
Health and commuter benefits
Company paid life & disability
20+ PTO days
401K and FSA plans
A fun team of Pandas to work with
Company
PandaDoc
PandaDoc enables users to create, deliver, and manage their teams’ quotes, proposals, contracts, and other sales collateral.
501-1000 employees
H1B Sponsorship
PandaDoc has a track record of offering H1B sponsorships. Please note that this does not
guarantee sponsorship for this specific role. Below presents additional info for your
reference. (Data Powered by US Department of Labor)
Distribution of Different Job Fields Receiving Sponsorship
Represents job field similar to this job
Trends of Total Sponsorships
2025 (1)
2024 (1)
2023 (1)
2020 (1)
Funding
Current Stage
Late StageTotal Funding
$56.94MKey Investors
Indico Capital PartnersOne PeakRembrandt Venture Partners
2025-12-16Series Unknown· $5.88M
2021-09-22Series C
2020-08-05Series B· $30M
Leadership Team
Mikita Mikado
CEO
Sergey Barysiuk
CTO, co-founder
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