Python - Data Analyst
Budget / SalaryHourly project
TypeFreelance project
LocationRemote
Posted1 hour ago
Projects
1. Sports Footwear Sales & Consumer Behavior
• Performed EDA using Python to uncover sales trends, pricing patterns, and customer behavior
• Identified key drivers of purchase decisions through demographic and rating analysis
• Built Power BI dashboards for sales performance and customer segmentation
• Delivered actionable insights via PowerPoint for pricing and marketing optimization
2. Ola & Uber Ride Booking Analysis
• Analyzed ride data using Python to evaluate booking trends and cancellation patterns
• Identified critical factors affecting driver and customer cancellations
• Developed Power BI dashboards to monitor KPIs and peak demand periods
• Presented data-driven recommendations to improve ride efficiency and reliability
3. Delhi Weather & AQI Analysis
• Conducted time-series analysis using Python to track weather and AQI trends
• Examined correlations between environmental factors and air quality levels
• Designed Power BI dashboards for AQI monitoring and seasonal insights
• Communicated findings through structured presentations for better interpretation
1. Sports Footwear Sales & Consumer Behavior
• Performed EDA using Python to uncover sales trends, pricing patterns, and customer behavior
• Identified key drivers of purchase decisions through demographic and rating analysis
• Built Power BI dashboards for sales performance and customer segmentation
• Delivered actionable insights via PowerPoint for pricing and marketing optimization
2. Ola & Uber Ride Booking Analysis
• Analyzed ride data using Python to evaluate booking trends and cancellation patterns
• Identified critical factors affecting driver and customer cancellations
• Developed Power BI dashboards to monitor KPIs and peak demand periods
• Presented data-driven recommendations to improve ride efficiency and reliability
3. Delhi Weather & AQI Analysis
• Conducted time-series analysis using Python to track weather and AQI trends
• Examined correlations between environmental factors and air quality levels
• Designed Power BI dashboards for AQI monitoring and seasonal insights
• Communicated findings through structured presentations for better interpretation
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