Product Data Analyst

This role supports the Data Analytics & Operations function within the Product Insights team by transforming product usage and behavioral data into clear, actionable insights. This role focuses on accurate data analysis, dashboard development, and KPI reporting to help monitor product health, feature adoption, and user engagement. 

This analyst contributes to scalable reporting practices and strong data governance while building expertise in product analytics within a fast-growing fintech environment. 

● Conduct analysis of product usage, feature adoption, user journeys, and engagement metrics to uncover actionable insights. 

● Build and maintain dashboards and recurring reporting that support product health monitoring and KPI tracking. 

● Support the implementation and validation of product instrumentation and tracking requirements.
● Assist in developing and maintaining clean, structured datasets for reliable reporting and analysis.
● Partner with Product, UX Research, and Engineering to answer business questions using quantitative data.

● Ensure data accuracy through validation, documentation, and adherence to metric definitions.
● Identify trends, anomalies, or risks in behavioral data and escalate findings appropriately.
● Contribute to documentation of analytics processes, definitions, and reporting standards.
● Perform other duties as assigned. 

● While performing the duties of this Job, the employee is regularly required to sit; use hands to type, handle, or feel and talk or hear 

● Specific vision abilities required by this job include close vision 

● Ability to occasionally lift/move up to 25 pounds 

● Individuals with a disability who are otherwise able to perform the essential functions of the job may request reasonable accommodation through the Human Resources department.

● Bachelor’s degree in Data Analytics, Statistics, Mathematics, Business, Engineering, or related field required, or equivalent combination of education and experience. 

● Familiarity with conducting analysis using code-based workflows (e.g., Python, SQL), with an emphasis on reproducibility, clarity, and version control. 

● Familiarity with basic ETL concepts and experience preparing structured datasets for analysis in collaboration with data engineering partners. 

● Ability to translate stakeholder questions or data requests into clearly defined analytical problems by identifying underlying objectives, constraints, assumptions, and appropriate methodologies. 

● Understanding of statistical concepts, basic experimentation design, and performance metrics. 

● Familiarity with data validation, governance, and metric documentation practices.