09/06/2022 updated
HA
100 % available
Senior Lead Data Scientist(PhD) with 13 years experience in industry and academics
Ankara, Turkey
Turkey
BSc and MSc in mechanical engineering, PhD in experimental data analysisPythonData ScienceMachine Learninganomaly detectionpredictive maintenance Supervised LearningUnsupervised LearningTime Series Analysisdeep learningBusiness Analytics
I have a great motivation and experience in extracting meaning from large datasets. I have had the chance to apply analytical techniques to business problems in different fields like transportation, aviation, defense, and finance. Having both academic and industrial expertise in data science, I have always approached the business problem with a systematic methodology, a journey starting with problem definition, data preparation and manipulation, data visualization, descriptive or predictive machine learning/statistic models as required for the problem solution. I am also experienced in leading junior-midlevel data scientists as well as teaching colleagues in data science field. I am very willing to apply my expertise in a new field, and a strong company where data driven technologies are rated as valuable. I want to support the business via data driven automated decision making processes.
Skills: Data analysis, analytics, data manipulation, anomaly detection, data science, visualisation, data mining, machine learning, time series analysis, predictive models, predictive maintenance, developed data analysis platforms, SQL, SPSS, SAS (Base, EG, Miner), R programming language, Phyton, PyQt, Minitab, Object Oriented Programming, coding, coding version control, Matlab, Matlab / SIMULINK, modelling and simulation, SSIS, Octave, Microsoft Office applications, MS Word, Excel, Powerpoint, Frontpage
Skills: Data analysis, analytics, data manipulation, anomaly detection, data science, visualisation, data mining, machine learning, time series analysis, predictive models, predictive maintenance, developed data analysis platforms, SQL, SPSS, SAS (Base, EG, Miner), R programming language, Phyton, PyQt, Minitab, Object Oriented Programming, coding, coding version control, Matlab, Matlab / SIMULINK, modelling and simulation, SSIS, Octave, Microsoft Office applications, MS Word, Excel, Powerpoint, Frontpage
Languages
GermanBasic knowledgeEnglishFluentTurkishFluent
Project history
The position involved development of analytical tools for automated data reporting, data
analysis and predictive analytics purposes. A data analysis platform was developed to analyse
missile flight data via a standardized methodology, including most types of data manipulation
and exploration techniques as selected by the user. Time series data analysis also included
anomaly detection methods to alert on visualized data and help decision making and root cause
analysis processes. The developed data analysis platforms were not only focused on flight, but
also on production and project management data for missiles. The developed tools had been
designed in line with data science methodology starting from problem definition, data
preparation, manipulation, visualisation, and development of predictive or descriptive analytical
methods as required by the business problem definition.
analysis and predictive analytics purposes. A data analysis platform was developed to analyse
missile flight data via a standardized methodology, including most types of data manipulation
and exploration techniques as selected by the user. Time series data analysis also included
anomaly detection methods to alert on visualized data and help decision making and root cause
analysis processes. The developed data analysis platforms were not only focused on flight, but
also on production and project management data for missiles. The developed tools had been
designed in line with data science methodology starting from problem definition, data
preparation, manipulation, visualisation, and development of predictive or descriptive analytical
methods as required by the business problem definition.
Teaching programming data mining techniques using Phyton to students at College of
Engineering and Natural Sciences.
Engineering and Natural Sciences.
The position involved development and application of data driven analytic technologies with
marketing insights for customer value management (CVM). Developed analytics was used to
target customers with high propensity to buy insurance products using statistical models. The
developed models have been proved to increase sales ratio by two-three times compared to
targeting random groups of customers. Analytical skills have also been applied to develop
segmentation models which help to group similar customers into unique segments such that
marketing actions from operations to product development can be designed for each segment
separately according to segment characteristics.
The position involved collaboration with international Cigna Analytics team in Hong Kong.
Collaborative work was also conducted with QNB Finansbank, our affinity partner, in terms of
enriching insurance dataset with further financial information from the bank database to develop
strong analytical solutions.
marketing insights for customer value management (CVM). Developed analytics was used to
target customers with high propensity to buy insurance products using statistical models. The
developed models have been proved to increase sales ratio by two-three times compared to
targeting random groups of customers. Analytical skills have also been applied to develop
segmentation models which help to group similar customers into unique segments such that
marketing actions from operations to product development can be designed for each segment
separately according to segment characteristics.
The position involved collaboration with international Cigna Analytics team in Hong Kong.
Collaborative work was also conducted with QNB Finansbank, our affinity partner, in terms of
enriching insurance dataset with further financial information from the bank database to develop
strong analytical solutions.