Develop an expert level understanding of Signify’s core product offerings and analytics technology.
Define, track, report out, and explain product metrics including performance and profitability.
Build and maintain robust data transformation models using dbt and utilize Claude Code to accelerate SQL development and technical documentation.
Build and maintain Power BI dashboards and reports to track product health, highlight insights, and monitor the success of product initiatives.
Architect Snowflake semantic views to power Snowflake Intelligence, enabling natural language data discovery for stakeholders.
Deploy and manage AI agents within the data warehouse to automate monitoring and proactive alerting of product performance anomalies.
Become a key partner with Product, Engineering, Operations and Analytics teams to drive key Signify objectives.
Be a champion of A/B testing and help stakeholders throughout the company design, analyze, and interpret A/B tests correctly.
Able to use alternative causal inferences techniques when A/B testing is not feasible.
Develop ROI projections for analytics projects to prioritize analytics deliverables by impact to the business.
Communicate progress, barriers, priority and budget regularly with leadership.
Tell compelling stories through data, articulating technical information to a non technical audience.

Bachelor’s degree in Statistics, Data Science, Business Analytics, Economics, Computer Science, Engineering, or a related technical field is preferred.
5+ of experience in a technical product analytics or data science role, with a proven track record of influencing product decisions through technical insights.
Experience with dbt (Data Build Tool) or similar analytics engineering tools to manage data transformations, version control (Git), and data documentation.
Experience using AI coding assistants such as Claude Code to streamline development and automate repetitive analytical tasks.
Build, develop and maintain dashboards and performance metrics that support key business decisions.
Experience with A/B testing, funnel analysis, and other statistical analysis methods, including regression, clustering, classification, and predictive modeling.
Advanced proficiency in SQL and Snowflake, and experience with Python or R for data analysis and modeling.

Affordable medical plan options
401(k) plan (including matching company contributions)
Employee stock purchase plan
No-cost programs for all colleagues including wellness screenings, tobacco cessation and weight management programs
Confidential counseling and financial coaching
Benefit solutions that address the different needs and preferences of our colleagues including paid time off, flexible work schedules, family leave, dependent care resources, colleague assistance programs, tuition assistance, retiree medical access and many other benefits depending on eligibility.

Senior Product Analyst

Key skills