Aleksandr Lipatev

• Team management and motivation • Collecting requirements and managing stakeholder expectations in a distributed company • Development and maintenance of data marts • Architectural considerations with regards to DWH • DB (Exasol) administration Tool set: Exasol (SQL + scripts), Pentaho Kettle for ETL, python for non-relational imports, docker, git, a bit of bash, Jenkins

• Extensive SQL development for Exasol and occasionally for Postgres • Development and maintenance of AWS services in BI area of responsibility • Development of data imports (Pentaho Kettle / python) • Building of docker images for BI needs • Automation of data quality control and compliance (GDPR) Tool set: Exasol (SQL + scripts), Pentaho Kettle for ETL, python for non-relational imports, docker, git, a bit of bash, Jenkins

• Using SAP BusinessObjects and other tools to provide enterprise reporting, self-service BI and data insights to business • Ad-hoc analytics and visualization • Mentoring collegues on BusinessObjects usage best practices, including intra-department seminars Tools used: • SQL (Oracle, Sybase, Hadoop) • R / Python (NumPy, SciPy, Matplotlib) • Web Intelligence (Webi), Universe Design Tool, Information Desing Tool, XCelsius, Report Conversion Tool, Query Builder, Desktop Intelligence (DeskI), Tableau

• Administration and development of corporate Oracle DWH (partitioning, performance tuning, ELT, space management, role structure): • Analysis of promo • Ad hoc analyses • Sales dynamics in different slices: CLTV, refuse reasons etc.

Support and development of corporate BI Systems: • OBIEE (10g, 11g) for Siebel Marketing, Answers, BI Publisher, Administration • IBM Cognos BI for enterprise reporting, Report Studio, Event Studio, Framework Manager • Expert knowledge of SQL and PL/SQL: writing and optimization of complex SQL queries, procedures, functions, packages, triggers.

Customer base segmentation Making forecasts of marketing actions’ effectiveness Analysis of open rate, CTR, money spending dynamics of SMS and Email campaigns Work with big data volumes – SQL queries to Data Warehouse

Periodic control of acceptance level for different customer segments Conducting analysis and forecasting results on acceptance level and payment behavior for launching different application form checks Data mining with the final goal to reduce credit risk. Controlling risks for Revolving business line, performing ad-hoc analysis by colleagues inquiries Scorecard development using SAS software for acceptance scoring and behavioral scoring

Mathematical and statistical modeling. Field presentations, comprehensive analysis of customers' data, writing analytical reports. Teaching customers and students to work with STATISTICA package and theoretical fundamentals of mathematical statistics and Data Mining. Preparing educational materials for study courses. Translation of diverse materials on data analysis.

Fundamental and applied mathematics; I also have a publication on multivariate statistics