• Experienced in IBM TM1 Planning Analytics, having strong business. • Analytical, conceptual and organizational skills, interest in statistics, data science and business analytics methods. • Have a passion for data science, machine learning and artificial intelligence. • Eager to develop my professional skills and curious to discover and implement new manners, technologies and tools especially in field of machine learning, statistic and computer science ecosystems, data analytics and business knowledge. • Demonstrated ability to work independently with minimal supervision. • Creating basic statistical models that can predict and analyse client`s behaviour, wants, and needs. • Ability to produce clear and accurate documentation. • Ability to work collaboratively with end users. ; I am experienced in statistical data analysis using SPSS. I try to integrate my strong statistical knowledge and skills that I learned in both undergraduate and graduate education with the subjects of Data Science. I am trying to provide a good understanding of machine learning, probability and statistics and the basics of NLP. I am trying to strengthen my intermediate-level SQL knowledge/experience from my IBM TM1 consulting job. For comfortable working, the ultimate goal is to have the ability to write complex, robust, reusable data SQL queries to handle any database and/or massive data sets. In order to call myself data scientist strictly, I am trying to learn scientific programming languages and frameworks such as Python, R, keras, tensorflow etc. for analytical coding, that is machine learning, predictive analytics and exploratory data analysis, to a level that I can work as a data scientist in any sector/industry. The ultimate goal is to be able to do projects with strong Python and R knowledge and machine learning related libraries such as Pandas, NumPy, SKlearn etc., thanks to the good mathematical and statistical foundations that I have. I am trying to learn Tableau, one of the data visualization and reporting tools. The ultimate goal is to enable the developed analytical reports to represent large, complex data sets through visual representation creating user-friendly graphs, charts, and animations. I am trying to have practical experience with methods such as statistical methods, isolation forest, SVM, RNN, LSTM and deep learning. ©