The mission of a Senior Data Analyst is to leverage data to optimize the pricing strategy of the platform. They are responsible for analyzing data, identifying trends, and making strategic recommendations to help set the correct prices for drivers and riders, considering factors like demand, supply, time of day, location, and more. Their goal is to ensure the pricing is competitive, fair, and beneficial for all parties involved, ultimately leading to increased platform usage and business growth.

Responsibilities:

•            Analyzing Pricing data to optimize pricing strategies, find improvement spaces, and find problems.
• Extracting data from primary and secondary sources using automated tools involves accessing various databases or web sources containing relevant data for the analysis.
• Covering pricing monitoring shifts ensures business metrics remain healthy and react accordingly.
• Cleaning and validating data for accuracy and quality: This involves removing corrupted or incomplete data, fixing coding errors or formatting issues, checking for outliers or anomalies, etc.
• Developing and maintaining databases and data systems: This involves organizing data in a structured and accessible format that can be easily queried or updated.
• Analyzing data using statistical methods and software: This involves applying descriptive or inferential statistics to summarize or test data patterns, trends, relationships, etc.
• Creating reports and dashboards to visualize and communicate findings: This involves using graphs, charts, tables, maps, etc., to display data results in an appealing and informative way that different audiences can understand.
  
• Plan and run pricing A/B tests to improve key KPIs
• Provide new detailed reports and maintain current pricing reports to ensure day-to-day business performance is running smoothly
• Work on new features for pricing and dispatching
• Enhancing data collection procedures to include information that is relevant for building analytic systems.

Requirements: 

• 2-3 years of experience in related fields.
  
• SQL expertise especially in getting data
• Proficiency in at least one programming language especially in data science like Python (working with libraries like pandas, sci-kit learn, NumPy
• Knowledge of the underlying mathematical foundation of statistics, optimization, and experimental design
• Storytelling with data capabilities
• Analytical Mindset, critical thinking and problem-solving skills
• Hardworking, creative and passion
• Familiarity with ML concepts and utilizing them is a plus.