About the Role

We are seeking a Staff Product Data Scientist to join our team at PandaDoc. This remote position allows you to leverage your expertise in data science to drive impactful business decisions. As a Staff Product Data Scientist, you will play a crucial role in fostering a data-driven culture within our organization. You will work closely with cross-functional teams to uncover insights that will shape our product strategy and enhance customer experiences.

What You'll Do

  • Lead the Experimentation Roadmap: Define and execute a strategic roadmap for measuring impact across PandaDoc, focusing on high-leverage business questions related to customer workflows and churn risk.
  • Design and analyze complex A/B tests and multivariate experiments, applying advanced methodologies such as Bayesian experimentation.
  • Utilize advanced causal inference techniques to assess scenarios where randomized controlled trials are not feasible.
  • Conduct deep dive analyses to uncover latent user behaviors and emerging trends, translating findings into actionable insights.
  • Develop and govern a unified Key Performance Indicator (KPI) framework that aligns product health metrics with business outcomes.
  • Collaborate with Data Engineering to build scalable experimentation tools and analytical frameworks.
  • Translate complex statistical findings into clear narratives for senior leadership, driving strategic decisions.
  • Mentor junior data scientists on best practices in statistical rigor and experimental design.

Requirements

  • 6+ years of experience in data science, economics, or product analytics, with a focus on experimentation and causal inference.
  • B.A. or B.S. in Mathematics, Statistics, Economics, Computer Science, or a related field; a Master's degree is preferred.
  • Expertise in causal inference methods and advanced statistical methodologies for A/B testing.
  • Proficiency in Python or R for statistical modeling, with experience in data science packages.
  • Expert-level proficiency in SQL and experience with data warehouses like Snowflake or Postgres.
  • Experience with data transformation tools such as dbt or Airflow is a plus.
  • Exceptional communication skills, with the ability to influence cross-functional partners.
  • Experience in a SaaS environment is preferred.

Nice to Have

  • Experience in product data science.
  • Familiarity with machine learning techniques.
  • Strong analytical and problem-solving skills.

What We Offer

  • Competitive salary up to $210,000.
  • Comprehensive health and commuter benefits.
  • 20+ PTO days and company-paid life & disability insurance.
  • 401K and FSA plans.
  • A supportive team culture with opportunities for career growth.
Language Requirements
EnglishC1
BasicIntermediateAdvancedNative
Why This Job8.5 of 10

This Staff Product Data Scientist role at PandaDoc offers a unique opportunity to drive data-driven decision-making in a supportive remote environment. With a competitive salary and strong growth potential, it's an attractive position for experienced data professionals.

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

Who Will Succeed Here

Proficient in Python and R for statistical modeling and machine learning, with a strong understanding of A/B testing frameworks to validate product changes.

Self-motivated and disciplined in a remote work environment, with excellent time management skills to balance multiple projects and collaborate effectively across teams.

Deep understanding of causal inference techniques and their application in real-world scenarios to derive actionable insights from complex datasets.

Learning Resources

Data Science Handbookbook

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
$140B
Annual Growth
30.0%
AI Adoption in Data Science
75%
Investment in Data Science Tools
+50%
Labour Demand for Data Scientists
+28%
Avg Salary for Staff Data Scientist
$150K

Skills & Requirements

Required
Data ScienceCausal InferenceA/B Testing
Growing in Demand
Deep LearningNatural Language Processing (NLP)Big Data Technologies (e.g., Spark, Hadoop)
Declining
Excel for Data AnalysisTraditional Statistical Software (e.g., SAS)

Domain Trends

Increased AI Integration
By 2025, 80% of data science projects will incorporate AI technologies, enhancing predictive analytics and automation.
Shift to Automated Machine Learning (AutoML)
AutoML tools are expected to reduce the time spent on model building by 50%, making data science more accessible to non-experts.
Focus on Ethical AI and Data Governance
In 2024, 60% of organizations will prioritize ethical AI practices and data governance frameworks to ensure compliance and trust.

Industry News

Loading latest industry news...

Finding relevant articles from the last 6 months

All job postings are automatically gathered by algorithms. We do not review or verify listings, be careful when applying and do not sign-in with iCloud or Google services.