• Conduct complex data analysis for building analytical data models for Data Science team
• Experience in Clickstream analysis to track the customer interactions on ECOM platforms
• Interpret data, analyze results, identify data quality issues upfront in the analysis phase
• Use complex SQL queries for dataset preparation for review with Business
• Collaborate with business and technical partners to understand and evaluate their requirements regarding data and determine the optimal way to gather and transform data for Business metrics
• Identify and define data quality improvements and collaborate remediation with partner teams
• Work closely with Data Engineers, Data Modelers and Quality Engineers
• Document detailed data mappings and data flows for Dev & QA team

Responsibilities:

1. Clickstream Analysis:
   • Gather, clean, and preprocess clickstream data from various sources.
   • Perform in-depth analysis of user navigation patterns, click paths, and interactions within our digital platforms.
   • Identify trends, anomalies, and areas for improvement in user engagement.
2. Data Visualization:
   • Create insightful and visually appealing dashboards, reports, and visualizations to communicate findings to stakeholders.
   • Utilize data visualization tools (e.g., Tableau, Power BI) to transform complex data into actionable insights.
3. User Behavior Insights:
   • Collaborate with cross-functional teams to understand business objectives and formulate data-driven hypotheses related to user behavior.
   • Analyze clickstream data to provide insights on user preferences, conversion rates, drop-off points, and other relevant metrics.
4. A/B Testing and Experimentation:
   • Design and execute A/B tests to evaluate the impact of website changes on user behavior.
   • Analyze and interpret the results of experiments to inform website optimization strategies.
5. Data Integrity and Quality:
   • Ensure data accuracy, consistency, and reliability by performing data validation and reconciliation.
   • Work closely with data engineering teams to address data quality issues and improve data collection methods.
6. Collaborative Reporting:
   • Collaborate with stakeholders, including marketing, product management, and UX/UI teams, to provide actionable insights and support data-driven decision-making.
   • Clearly communicate findings to both technical and non-technical audiences.
7. Continuous Learning and Innovation:
   • Stay up-to-date with industry trends, best practices, and emerging technologies in data analytics and clickstream analysis.
   • Explore innovative approaches to enhance the depth and breadth of clickstream data analysis.