Company
SaaS
ProductDataAnalyst
Neural analysis suggests this role is
optimal for Senior candidates.
“Product Data Analyst. Skills: Product analytics, User behavior analysis, A/B testing, Data-driven recommendations. Act as analytics partner to product managers. Support analysis of product usage”
What You'll Achieve.
Influence product roadmap decisions; Provide data-backed recommendations on what to build; Provide data-backed recommendations on what to improve; Provide data-backed recommendations on what to deprioritize
Industry & Context.
Analytical approaches; Identify analytical opportunities
What They're Looking For.
Must Have
5+ years of experience in product analytics, Experience analyzing user behavior, Deep expertise in SQL, Understanding of statistical methods, Proven experience designing, running, and interpreting A tests, Experience defining event tracking schemas, Ability to independently identify high-impact analytical opportunities, Excellent communication skills, Product intuition
Nice to Have
Python experience for data analysis is a plus, Familiarity with causal inference methods is an advantage, Familiarity with experimentation platforms is an advantage, Experience working with technical or developer-focused products is a plus
What You'll Do.
Act as analytics partner to product managers
Support analysis of product usage
Support analysis of user behavior
Support analysis of feature performance
Conduct advanced product analyses
Identify key behavioral drivers
Deliver cross-product insights
Deliver segment-level insights
Co-develop hypotheses with product managers
Design analytical approaches
Influence product roadmap decisions
Provide data-backed recommendations
Ensure statistical rigor
Ensure actionable outcomes
Partner with engineering on event instrumentation
Partner with product on event instrumentation
Partner with engineering on tracking design
Partner with product on tracking design
Partner with engineering on data quality improvements
Partner with product on data quality improvements
Identify opportunities for deeper analysis proactively
Surface recommendations
Translate complex data findings
Support decision-making
Contribute to improving analytical standards
Contribute to improving methodologies
Contribute to improving experimentation practices
How You'll Work.
Team & Collaboration
Product managers; Engineering teams; Product teams
Communication Scope
Clear narratives; Decision-ready insights
Full Job Description
## Accountabilities Act as the dedicated analytics partner to product managers, supporting deep analysis of product usage, user behavior, and feature performance. Conduct advanced product analyses across activation, onboarding, adoption, retention, and expansion to identify key behavioral drivers. Deliver cross-product and segment-level insights that provide a broader perspective beyond individual product squads. Co-develop hypotheses with product managers and design analytical approaches to validate product decisions. Influence product roadmap decisions by providing clear, data-backed recommendations on what to build, improve, or deprioritize. Design, evaluate, and interpret A/B tests and experiments, ensuring statistical rigor and actionable outcomes. Partner with engineering and product teams on event instrumentation, tracking design, and data quality improvements. Identify opportunities for deeper analysis proactively, surfacing insights and recommendations even without formal requests. Translate complex data findings into clear, structured narratives that support decision-making at all levels. Contribute to improving analytical standards, methodologies, and experimentation practices across the product organization. Requirements 5+ years of experience in product analytics, data analysis, or related roles within B2B SaaS environments, ideally in product-led growth companies. Strong experience analyzing user behavior, product funnels, activation metrics, retention drivers, and feature adoption. Deep expertise in SQL and strong familiarity with modern data stacks (e.g., BigQuery, dbt, Metabase or equivalent tools). Strong understanding of statistical methods, including hypothesis testing, bias detection, and experimental design. Proven experience designing, running, and interpreting A/B tests and product experiments. Experience defining event tracking schemas and collaborating with engineering teams on instrumentation. Strong ability to independently identify high-
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