Istanbul, Istanbul, Türkiye
Senior Data Analyst at PwC Turkey with approximately 5 years of experience in analytics engineering, data modeling, and enterprise reporting solutions. Specialized in building end-to-end analytics platforms using Microsoft Fabric and Power BI, including automated pipelines, data transformation, semantic modeling, and dashboarding. Experienced in developing machine learning–driven solutions and data applications using Python. Delivered scalable analytics solutions across automotive, manufacturing, and finance sectors. Formerly gained 2 years of experience in the fashion retail industry. Microsoft Certified: Fabric Data Engineer Associate (DP-700). Microsoft Certified: Fabric Analytics Engineer Associate (DP-600).
• Nissan Automation Project Automated dashboards from the Nissan Dashboard Project using Microsoft Fabric pipelines for ingestion, transformation, and refresh. Led and supervised the development of Power Apps upload interfaces and Power Automate workflows, ensuring effective end-to-end automation and alignment with business requirements. Developed and managed Fabric pipelines integrating multiple data sources with minimal manual effort. Led the project technically and functionally, mentoring the team and managing customer communication end-to-end. • Nissan Dashboard Project Led the development of 10 interactive Power BI dashboards supporting cross-functional business insights. Personally delivered 3 end-to-end dashboards, ensuring data accuracy and high-quality visualization. Mentored a team of 5 junior analysts and coordinated daily delivery activities. Integrated dashboards with enterprise databases via Microsoft Fabric for automated and near real-time reporting. • Sabancı Holding Financial Analytics Project Led all Microsoft Fabric activities, including data extraction, modeling, and transformation across environments. Designed and operated daily scheduled pipelines using medallion architecture (DEV / TEST / PROD). Managed monthly production releases and ensured data quality, stability, and scalability. Supported Power BI financial dashboards with dynamic period selection and inflation-adjusted analysis for multi-entity reporting.
• Declaration of Conformity Automation Tool: Designed and developed an end-to-end Declaration of Conformity automation tool using Python and Streamlit. Built a self-updating data mechanism that automatically retrieves and refreshes regulatory data from European Commission websites, ensuring data accuracy and up-to-dateness. Enabled users to upload datasets for validation, automating a traditionally complex and time-consuming compliance control process. Implemented advanced data verification and validation logic to detect inaccurate, outdated, or non-compliant records. Generated detailed validation reports highlighting erroneous records and compliance issues for end users. Delivered a user-driven, interactive application with no direct market equivalent, significantly reducing manual effort and operational risk. • Cyber Attack Monitoring Project: Designed and developed an interactive Cyber Attack Monitoring Dashboard using Python and Streamlit. Integrated real-time API connections to retrieve live utilization and usage metrics of bot virtual machines used by the cyber security team. Visualized live and historical utilization data dynamically based on user-defined parameters. Implemented background processes to validate, cross-check, and persist all incoming data into a structured database. Enabled continuous monitoring and analysis of resource consumption, supporting operational visibility and proactive decision-making for the cyber team. • Market Prioritization Dashboard: Investment-Oriented Market Prioritization Dashboard study conducted for a company working in the renewable energy sector. Study outcomes visualized was made on Power BI. • Insight Dashboard: A dashboard was created where audit employees can get the first insights into the audited company in order to speed up their work before auditing. The dashboard was made by Power BI.
Mainly responsible for end-to-end data analytical processes containing ML projects regarding to the business needs. • Responsible for store grading processes which is management of products in stores using data analytics (all developments and upgrades). • Also responsible for developments and outcomes of store replenishment systems which automatically sends products from the warehouse to the stores in need. • Primarily responsible for project developments which are: • Feature Selection Project: Determining which features of products with hundreds of features have a positive or negative effect on performance of the products with machine learning methods and implementing to the supply systems. Random forest algorithm is used in the project. • Product Profiling Project: Creating store-product profiles for shipping systems using all required data about store-products. • Store Segmentation Project: Clustering the products in the stores by using K-Means algorithm. • Detection of Special Days in Retail Project: Determining the days that increase/decrease sales and require special attention in terms of supply chain in retail with historical data analysis. • Optimization Inter-Store Transfer Cost Projects: Calculations of the cost and important metrics of inter-store transfer and revising the inter-store transfer process according to the outputs obtained from the project.