Georgiana Motoi

•Analyze performance of marketing campaigns •Use of statistics to understand player behavior, type/ segments of players• Build and maintain regular reports to monitor the performance of activity • Communicate key insights through internal reports, presentations to support the decision-making• Acquire data from internal databases using SQL / Impala queries and R statistical software• Use R and Excel for exploratory data visualization, statistical significance testing and other analytical purposes

• Develop customer portfolio analyses and reports • Analyze customer data to support effective marketing campaigns and customer contact initiatives• Build up and implement customer segmentation models (clustering ) and client profile •Identify trends and patterns in customer data •Develop customer behavior prediction models (machine learning using R programming – Regression, Classification, Tree Methods, Unsupervised Methods, Forecasting ) •Analyze NPS data •Query data from internal data structures;

• Statistical analysis of data (Regression; factor; discriminant; segmentation; cluster)) • Data analysis of projects assigned to marketing scientists (tools) • International communication with GfK Marketing Sciences team (methodology, tools) • Support for researchers / client service with methodology and reports • Support for data processing with non-standard data analysis and improving • Training and workshop for clients (technical/ statistics expertise) • Statistical consultancy

• Assignment of analysts to quantitative projects • Monitoring projects stage and quality standards • Training and workshop for data analysts • Setting yearly department/ individual objectives • Recruitment • Communication with operational teams (field, programmer, researcher) • International communication on projects and statistical issues Team: 12 Data analysts (3 seniors, 4 executives, 3 juniors, 2 assistants) Projects: Data Analysis Handbook; Standardization; Support - Project Manager

• Database management using SPSS commands • Checking and cleaning of SPSS data • Generating Excel tables from SPSS database • Validation and analysis of results figures • Sampling • Statistical analysis of data (Regression; discriminant; segmentation;cluster) • Cooperation on projects (research, fieldwork, programmers) • Testing data entry forms • Supervising and training for assistants/ juniors • Providing statistical expertise • Improve process of data analysis

• Database management using SPSS commands • Checking and cleaning of SPSS data • Generating Excel tables from SPSS database

Principal subjects covered- Research Methodology, Statistics, Statistical Software (SPSS), Data Analysis, Marketing, Economics, Accounting, Mathematics