Giorgi Sabadze

Build a Business Intelligence strategy and function to deliver accelerated growth across the business areas. Build the reporting of financial modelling. Responsibility of data standards, analytical methodologies including econometric modelling, predictive modelling, segmentation, reporting, customer analytics and descriptive statistics. Lead the team to iteratively improve data capability and data architecture to support the BI mission.

Participate in the full lifecycle of an analytics or BI project: from gathering, understanding the requirements to creating the functional design, architecting the solution, supervising the detailed technical design and implementation. Delivering high-quality reporting and insights through automation. Managing underlying data sources to allow quick and efficient data extracts to support analysis. Lead the strategic vision of the Analytics team as well as a clear roadmap for the business using data.

Assemble complex data sets that meet business requirements. Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc. Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using SAS, SQL and Other ‘big data’ technologies. Build analytics tools that utilize the data pipeline to provide actionable insights.

Interpreting data, analyzing results using statistical techniques and providing ongoing reports. Developing and implementing databases, data collection systems, data analytics and other strategies that optimize statistical efficiency and quality. Identifying, analyzing, and interpreting trends or patterns in complex data sets. Presenting results to management.

Analyzing Large Data, Building Complex CRM Campaigns and Strategy Plans for individual customers based on their purchasing history and other data. Providing a valuable insights into customers’ behavior to identify their preferences and tailor online offers to individual customers. Correlating customer purchase history with exposure to marketing campaigns or frequency of sales calls. Reporting, Data Mining, QUERY, Automation, Optimization of Operations. Visualization of Results.