Product Data Analyst

We’re looking for a talented Data Analyst to join our team, where you’ll directly report to the Product Data Manager. In this role, you’ll collaborate closely with a skilled group of product data analysts and product managers to provide actionable insights that drive key product decisions and shape the future of SnappShop through data-driven strategies.

Duties:

• Identify Opportunities: Lead data-driven projects that uncover new opportunities and insights, driving the development of innovative product features and capabilities.
• Ensure Data Excellence: Review dashboards and reports generated by other team members, ensuring high-quality, reliable data that informs decision-making.
• Monitor KPIs: Play a key role in defining, tracking, and reporting on KPIs across the company and product teams. Build intuitive dashboards and visualizations to make data accessible and actionable for stakeholders at all levels.
• Evaluate Feature Performance: Contribute to evaluating the success of newly launched features using A/B testing and other data-driven methods. Define success metrics to ensure features create real value for customers.
• Contribute to Data Products: Take an active role in building and refining SnappShop’s data products, including data warehouses, algorithms, and analytics infrastructure.

Requirements:

• Experience: While prior experience as a data analyst is a plus, we value passion and a willingness to learn. If you're early in your career but bring strong analytical skills and have a solid understanding of data manipulation, analysis, and visualization, we’d love to hear from you.
• Education: A bachelor's degree in a quantitative field such as Data Science, Engineering, Economics, Mathematics, or related disciplines.
• Technical Skills: Proficiency in SQL, Spark, and programming languages such as Python and R  is preferred, but not a hard restriction. 
• Communication: Strong verbal and written communication skills are essential to present complex data insights in a clear, concise, and actionable manner.
• Attention to Detail: A strong eye for detail with the ability to spot trends, anomalies, and patterns in data to derive meaningful insights.