Product Analyst

Easy Pay

- comprehensive market research to identify industry trends, customer needs, and competitive landscape, providing insights for product development and positioning - Collaborate with Product Managers, UX/UI Designers, and other stakeholders to identify data-driven opportunities for product improvements - Collect, clean, and analyze large datasets related to product performance, user engagement, and business KPIs (e.g., conversion rates, retention, engagement, churn rates, etc.) - Define, track, and evaluate product performance metrics, identifying trends and recommending strategic improvements - Conduct A/B testing and experimentation to evaluate new features and optimize user experience - Develop and maintain interactive reports, dashboards, and visualizations to provide actionable insights - Use data analytics tools to extract meaningful trends - Monitor customer feedback, surveys, and NPS to understand pain points and improve user satisfaction - Collaborate with business and marketing teams to measure the impact of campaigns on product engagement - Ensure data accuracy, integrity, and consistency across different platforms - Work closely with stakeholders to gather and document product requirements, translating them into clear and actionable user stories or product specifications - Use different tools to query and manipulate data efficiently

- Bachelor’s degree in Data Science, Statistics, Business Analytics, Economics, Computer Science, or a related field - 2+ years of experience as a Product Analyst, Data Analyst, or similar role in a digital product-driven company (preferably in fintech) - Experience working with large-scale datasets - Strong proficiency in SQL and experience with data visualization tools ( - Experience with programming languages such as Python or R for data analysis - Understanding of A/B testing methodologies and experimentation techniques - Excellent problem-solving and critical-thinking skills - Strong communication skills to present data insights to both technical and non-technical audiences - Ability to work independently and in a team-oriented environment - Familiarity with product analytics tools - Understanding of business metrics, product KPIs, and customer journey analytics - Knowledge of statistical modeling, and machine learning techniques is a plus

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