• Experienced in designing and implementing end-to-end supervised & unsupervised machine learning models using Python.• Built predictive models and data-driven analyses to support strategic business decisions.• Built CI/CD Pipelines using Azure DevOps Pipelines (YAML) and Databricks Clusters & Jobs & Notebooks. (REST API, Databricks CLI)• Improved performance by identifying potential claims using supervised machine learning techniques of Gradient Boosting (CatBoost, XGBoost) and Decision Tree / RF. • Created Python package to automate model training process, including compare/monitor model performance with different classification & regression algorithms, hyper-parameter optimization, log performance metrics and artifacts using MLflow and Azure ML. • Provide testing, deployment, maintenance, and performance assessment of existing predictive models.• Certified as MS Azure Data Scientist with running data experiments, train, optimize, deploy machine learning models on Azure Machine Learning and Azure Databricks.• Build customer-facing reporting tools to provide insights and metrics which track ML model prediction performances by using Power BI. • Developed complex SQL queries using joins, sub queries and correlated sub queries to retrieve data from MS SQL database.

• Designed ETL process dealing with different data sources and loaded data into target data sources with manipulations using Python libraries.• Developed complex SQL queries using joins, sub queries and correlated sub queries to retrieve data from MS SQL database.• Creating Reports and Dashboards by using different BI Tools (Power BI, Salesforce Reporting)• Execute data migrations and data quality efforts focused on completeness, standardization, and deduplication.• Retrieve and analyze data using Data Loader, DemandTools and other data management/BI systems.

• Developed complex SQL queries using joins, sub queries and correlated sub queries to retrieve data from the database.• Designed ETL process dealing with different data sources and loaded data into target data sources by performing transformations using Python libraries.• Designed and developed Power BI graphical and visualization solutions with business requirement documents and plans for creating interactive dashboards.• Developed VBA-driven tool to maintain and update sales territories to help support sales team.

Data Science - Part Time• Instructed 35 students on descriptive statistics, elementary probability rules, sampling, distributions, confidence intervals, correlation, regression and hypothesis testing, hands-on learning of applications using Python libraries and Excel.• Application of statistical concepts and techniques to a variety of problems in IT areas and other disciplines, using statistical and other packages for simple data analysis. • Course topics include descriptive statistics, elementary probability rules, sampling, distributions, confidence intervals, correlation, regression and hypothesis testing.

• Analyzed performances of business processes and users according to KPI values to improve operational efficiency by developing complex SQL Queries using joins, sub queries and correlated sub queries. • Created complex Triggers, Tables, Views and SQL Joins and other statements to maintain referential integrity and implement complex business logic.• Monitored performance and optimized SQL queries for maximum efficiency.• Experienced in ETL processes involving migrations and in sync processes between two databases.• Experienced in maintaining one to many and many to one relationship while moving data betweentwo databases.• Experienced designing visual report solutions, including dashboards and visualization/dashboard tools.• Extracted business process and user performances from web-based BPM Tool as XML and loaded the data into target data sources by performing different kinds of transformations using SQL Server.• Extracted data from data sources and created data mapping documents to support the development of database for risk modeling and reporting.• Designed/Implemented business processes to improve operational efficiency using JavaScript, XML, XPath.• Developed and implemented Electronic Data Management System (EDMS), transitioning organization from paper document approval to electronic which decreased processing time by 80%.• Hands-on experience in deploying/testing Web Services for API Calls (SOAP, REST) using SOAPUI.• Provided support during roll out of new tools through delivering trainings, implementation, feedback.• Followed Agile methodology, participated in daily SCRUM meetings and Retrospectives, achieved each SPRINT deliverables.• Execute test of controls for each process and documenting the results to Confluence & JIRA.

Leading brand in the apparel and fashion sectors in Turkey with 464 stores, $500+M annual and 11.000+ employees• Developed categorical financial budget plans to achieve sales and profit goals using Excel (Pivot Tables, Macros and complex Formulations), BI & OLAP cube reports and reported to the C-Level.• Demand forecasting based on historical performance and recommend actions comparing with historical real performance data from OLAP Cubes.• In pre-season and in-season OTB and financial planning, replenishment, assortment, inventory forecasting and merchandise allocation for 800+ SKU's.• Formulated 10%+ Sales growth and 5%+ Inventory turnover through sales reports, markdown strategies.

• Developed categorical financial budget plans to achieve sales and profit goals using Excel (Pivot Tables, Macros and complex Formulations), BI & OLAP cube reports and reported to the C-Level.• Demand forecasting based on historical performance and recommend actions comparing with historical real performance data from OLAP Cubes.• In pre-season and in-season OTB and financial planning, replenishment, assortment, inventory forecasting and merchandise allocation for 800+ SKU's.• Formulated 10%+ Sales growth and 5%+ Inventory turnover through sales reports, markdown strategies.

Project: Identification of Customer Clustering Criteria by using WEKA / K-means Clustering

Project: Investigation of Factors Affect Man-Hour Durations of Maintenances