تحلیلگر ارشد داده

Job Description

What you will do: ● You design analytics data structures and custom events (user behavior, financial) for e-commerce applications (mobile, and web). ● You design efficient events flow and define metrics and KPIs for e-commerce data. ● You verify the implementation of events on the client-side (mobile, and web). ● You monitor data and make queries, reports, and dashboards using our analytical platforms. ● You connect databases to our analytical platforms. ● You verify the implementation of analytical and marketing platforms especially push notification automation. Responsibilities: ● Using automated tools to extract data from primary and secondary sources. ● Removing corrupted data and fixing coding errors and related problems. ● Developing and maintaining databases, and data systems – reorganizing data in a readable format. ● Performing analysis to assess the quality and meaning of data. ● Filter data by reviewing reports and performance indicators to identify and correct code problems. ● Using statistical tools to identify, analyze, and interpret patterns and trends in complex data sets that could be helpful for the diagnosis and prediction. ● Assigning numerical value to essential business functions so that business performance can be assessed and compared over periods of time. ● Analyzing local, national, and global trends that impact both the organization and the industry. ● Preparing reports for the management stating trends, patterns, and predictions using relevant data. ● Working with programmers, engineers, and management heads to identify process improvement opportunities, propose system modifications, and devise data governance strategies. ● Preparing final analysis reports for the stakeholders to understand the data-analysis steps, enabling them to take important decisions based on various facts and trends. Another integral element of the data analyst job description is EDA or Exploratory Data Analysis Project. In such data analyst projects, the analyst needs to scrutinize data to recognize and identify patterns. The next thing data analysts do is use data modeling techniques to summarize the overall features of data analysis.