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Lumin Digital is a FinTech company whose innovative digital solutions help financial institutions engage their customers and grow. The company has hired in the
Product Data Analyst
Location
United States
Posted
83 days ago
Salary
$125K - $145K / year
Seniority
Senior
Job Description
Product Data Analyst
Lumin Digital
• 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.
Job Requirements
- Bachelor’s degree in Data Analytics, Statistics, Mathematics, Business, Engineering, or related field required, or equivalent combination of education and experience.
- 3–5 years of experience in product analytics, business intelligence, or data analysis.
- Hands-on experience with product analytics or web analytics platforms (e.g., Pendo, Google Analytics, Amplitude, or similar).
- Experience building dashboards using data visualization platform tools (Power BI, Tableau, QuickSight, etc.).
- Experience working with cross-functional teams in product-led organizations preferred.
- Exposure to experimentation analysis, A/B testing, or behavioral analytics preferred.
- Experience in fintech, digital banking, or SaaS environments preferred but not required.
- 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.
- Ability to translate data findings into clear, concise summaries for stakeholders.
- Strong attention to detail and commitment to data accuracy.
- Organized and able to manage multiple requests in a fast-paced environment.
- Curious and proactive in identifying patterns or inconsistencies in data.
- Comfortable working cross-functionally with Product Management, Design, UX Research, and Engineering.
- Effective communicator capable of explaining analytical findings to both technical and non-technical audiences.
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