Priori is seeking a Product Analyst to join our Product team and help shape data-informed strategy and execution. You will work closely with Product Managers, Engineering, Design, and GTM stakeholders to define success metrics, build trusted reporting, and deliver analyses that guide prioritization, experimentation, and product improvements.

Responsibilities will include:

• Partnering with Product, Engineering, and Business teams to define success metrics (north star, KPIs, leading indicators) and build measurement plans for new features
• Creating and maintaining dashboards, reporting, and self-serve analytics for stakeholders
• Performing deep-dive analyses to understand user behavior, funnel performance, retention, and feature adoption
• Designing and analyzing experiments (A/B tests) and quasi-experimental analyses; communicating results and recommendations
• Building and improving datasets (tables/views), data models, and documentation to ensure trusted metrics and definitions
• Cleaning, validating, and standardizing raw data from multiple sources to ensure accuracy, consistency, and readiness for analysis and reporting
• Identifying data quality issues, investigating anomalies, and partnering with Data Engineering to improve instrumentation and tracking
• Translating ambiguous questions into structured analyses, and presenting findings to both technical and non-technical audiences
• Contributing to the team’s analytics standards: metric governance, data definitions, and best practices

You’re a great fit if you:

• Have 4+ years of experience in product analytics, business intelligence, or a similar data-focused role
• Possess strong SQL skills and experience working with relational databases and large datasets
• Are proficient with a BI tool (e.g., Looker, Tableau, Power BI, Mode) and comfortable building dashboards that drive decisions
• Have solid foundations in statistics and experimentation (hypothesis testing, confidence intervals, power, bias/limitations)
• Have experience analyzing product funnels, cohorts/retention, and segmentation
• Communicate insights, tradeoffs, and uncertainty clearly to both technical and non-technical audiences
• Demonstrate high ownership and curiosity; comfortable in a fast-moving, iterative product environment

Nice to have:

• Experience with Python or R for analysis (pandas, notebooks) and/or dbt for data modeling
• Familiarity with product event tracking (e.g., Segment, Amplitude, Mixpanel) and instrumentation best practices
• Experience with data warehouses (e.g., Snowflake, BigQuery, Redshift) and ELT pipelines
• Exposure to machine learning concepts or predictive analytics (not required)