Senior Product Analyst

PandaDoc

4d

About The Position

As a Senior Product Analyst at PandaDoc, you will be a critical analytical partner, working closely with Product Managers, Engineers, and Designers to drive data-informed decisions within a specific product domain. This role focuses on applying analytical rigor, executing deep dive analyses, and interpreting experiment results to provide clear, actionable insights. You will support the measurement of product success and leverage your expertise to influence strategic product direction in an often ambiguous environment. You will report to the Director of Product Data and act as a reliable thought partner to your cross-functional product team, ensuring alignment between data insights and iterative product decisions.

Requirements

• Experience: 4+ years of professional experience in an applied product analyst or business intelligence role, with a proven track record of leveraging data to influence product strategy and drive business impact.
• Education: B.A. or B.S. in Mathematics, Statistics, Economics, Computer Science, or a related quantitative discipline.
• Experimentation & Measurement: Demonstrated experience in the design, measurement, and interpretation of A/B tests, including defining appropriate metrics and communicating statistical significance and practical relevance.
• Data Storytelling: Expertise in using BI tools (e.g., Tableau, Looker, Hex) to create impactful dashboards and data visualizations that communicate complex insights clearly.
• Programming: Advanced proficiency in SQL for complex querying, data manipulation, and extraction. Proficiency in Python or R is a strong plus.
• Analytical Methods: Strong knowledge of statistical concepts (e.g., hypothesis testing, confidence intervals) necessary to perform thorough exploratory data analysis, produce timely insights, and provide actionable recommendations.
• Data Tools: Expert-level proficiency in SQL and experience working with established data warehouses (e.g., Snowflake, Postgres).
• Strategic Communication & Influence: Possesses exceptional communication, presentation, and data storytelling skills with a consistent record of influencing cross-functional partners and leadership at the team level, particularly in navigating and driving consensus in unstructured or ambiguous environments.
• Thrive in Ambiguity: Ability to navigate significant ambiguity, translate complex business questions into clear analytical frameworks, and manage multiple competing priorities in a fast-paced environment.

Nice To Haves

• Relevant Experience: Experience in a SaaS domain and a strong focus on Product Analytics are strongly preferred.

Responsibilities

• Analytical Deep Dives: Execute complex analytical deep dives on key product areas (e.g., adoption, activation, engagement, retention, or monetization) to uncover root causes, identify opportunities, and translate findings into clear, actionable recommendations for product teams.
• Experimentation Execution: Partner with product teams to design experiments (e.g., A/B tests), define success metrics, and ensure proper implementation. Communicate the true impact and causality of product changes to stakeholders.
• Metric Monitoring and Reporting: Proactively monitor product KPIs and health metrics. Develop dashboards, reports, and clear visualizations using BI tools (e.g., Tableau, Looker, Hex) that enable product teams to monitor their health metrics independently.
• Data Advocacy and Influence: Translate analytical findings into compelling business narratives for cross-functional partners. You will advocate for the value of experimentation within your product area.
• Measurement Support: Support the definition, monitoring, and governance of the Key Performance Indicator (KPI) framework within your scope, mapping low-level product health metrics to high-level business outcomes.
• Analytical Rigor: Apply rigorous analytical methodologies to ensure the reliability and validity of product measurements, including selecting appropriate statistical tests for analysis.
• Collaboration and Guidance: Provide guidance to peers and stakeholders on best practices for data exploration, visualization, and reporting.
• Data Partnership: Work closely with Data Engineering and Product Engineering to ensure data quality, reliable instrumentation, and the availability of data needed for analysis.

Benefits

• Our benefits include tremendous career growth opportunities, a competitive salary, health and commuter benefits, company paid life & disability, 20+ PTO days, 401K and FSA plans, and of course, a fun team of Pandas to work with!

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Number of Employees: 501-1,000 employees