Talantix.io
PandaDoc•05.03.26
AI SCORE 8.5

Staff Product Data Scientist - Remote Opportunity

$120K–$150K/year
RemoteData Science & Analytics
Causal Inference•A/B Testing•Python•R•SQL•Data Analysis•Statistical Modeling

About the Role

We are seeking a Staff Product Data Scientist to join our team at PandaDoc. This remote opportunity allows you to become a senior analytical leader, deeply embedding yourself in our product and business data to uncover non-obvious insights and drive actionable recommendations. As a Staff Product Data Scientist, you will play a crucial role in championing and driving the organizational shift toward a data-driven culture.

What You'll Do

  • 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 Bayesian experimentation.
  • Apply advanced causal inference techniques to scenarios where randomized controlled trials (RCTs) are infeasible.
  • Conduct complex, proactive, and exploratory analysis to discover latent user behavior and emerging trends.
  • Define, instrument, and govern a unified Key Performance Indicator (KPI) framework that maps low-level product health metrics to high-level business outcomes.

Requirements

  • 6+ years of professional experience in applied data science, economics, or product analytics.
  • 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.
  • Expertise in advanced statistical methodologies for A/B testing.
  • Advanced proficiency in Python or R for statistical modeling.

Nice to Have

  • Experience with data transformation and workflow management tools such as dbt, Airflow, or Databricks.
  • Experience in a SaaS domain with a strong focus on Product Data Science.

What We Offer

  • Competitive salary with tremendous career growth opportunities.
  • Health and commuter benefits, company paid life & disability.
  • 20+ PTO days, 401K, and FSA plans.
  • A fun team culture with creative virtual team-bonding events.
  • Work-life balance and a commitment to integrity & transparency.
Why This Job8.5 of 10

This remote Staff Product Data Scientist role at PandaDoc offers a unique opportunity to lead data-driven initiatives and experimentation strategies. With a competitive salary and a supportive team culture, it's an attractive position for experienced data scientists.

Salary Range
Required
0/1
Optional
0/1
Bonus
0/1

Who Will Succeed Here

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Proficient in advanced statistical techniques such as causal inference and A/B testing, with a strong command of tools like Python and R for data manipulation and analysis.

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Self-motivated and results-driven, thriving in a remote work environment where independent problem-solving and proactive communication are essential to drive data-driven decisions.

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Extensive experience in data analysis with a strategic mindset, able to translate complex data findings into actionable insights for product development and organizational growth.

Learning Resources

→Causal Inference: A Practical Guideguide
→Introduction to A/B Testing with Pythonarticle
→Data Science and Machine Learning Bootcamp with Rcourse

Career Path

Staff Product Data Scientist(Now)→Lead Data Scientist(1-2 years)→Director of Data Science(3-5 years)

Market Overview

Market Size 2024
$3.5B
Annual Growth
15.2%
AI Adoption
72%
Investment
+40%
Labour Demand
+25%
Avg Salary
$135K

Skills & Requirements

Required
Causal InferenceA/B TestingPython
Growing in Demand
Machine LearningData Visualization (Tableau, Power BI)Bayesian Statistics
Declining
Excel for Data AnalysisTraditional Regression Techniques

Domain Trends

Increased Use of Automated A/B Testing
Over 60% of companies are adopting automated A/B testing frameworks to improve efficiency and reduce bias in experimental design.
Shift Towards Causal Machine Learning
The use of causal machine learning models has increased by 30% as organizations seek to derive actionable insights from data beyond correlation.
Integration of Data Science in Product Development
Around 55% of product teams now include data scientists in their workflow to inform product decisions, indicating a growing trend towards data-driven product strategies.

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