Istanbul, Istanbul, Türkiye
Experienced data and AI professional with a strong academic background and proven success in leading AI/ML and data initiatives across diverse industries. Expertise in platforms such as Azure, AWS, and open-source tools, driving the development of scalable data pipelines and AI solutions. Led high-performing teams, including data engineers, data scientists, and MLOps engineers, while managing end-to-end AI projects and developing data-driven strategies that optimize operations and improve decision-making. With extensive experience in data and AI, he excels in aligning technical solutions with business objectives, mentoring teams, and fostering innovation to deliver impactful AI solutions.
Leading AI initiatives across a group of functional units—Product Development, Implementation & Delivery Excellence, and Agentic AI Excellence—driving scale and continuous improvement of AI products and services.
Spearheaded end-to-end AI initiatives, managing the full lifecycle from pre-sales and consulting to development, deployment, and operationalization of AI products and services, with expertise in advanced analytics, optimization, machine learning, and generative AI, by leading and closely collaborating with a high-performing team of ~20 data scientists and AI/MLOps engineers. ■ Built and structured a high-performing AI team with dedicated sub-teams for AI/MLOps, productization, execution, and R&D, aligning resource allocation, skill development, and budget ownership with strategic product development goals. Maintained a strategic AI solution roadmap, managed delivery timelines, validated business cases, ensured go-to-market readiness, and embedded expertise across the teams. ■ Delivered 50+ AI and data-driven projects across FMCG, Retail, Automotive, Energy, and ICT sectors, spanning advanced analytics, NLP, computer vision, and 20+ generative AI projects, and led the end-to-end development of AI solutions in 2 software products from concept to market. ■ Oversaw a Generative AI transformation initiative across all group companies, delivering 50+ POCs and MVPs, leading workshops, and giving seminars to business and technical stakeholders to accelerate adoption and drive enterprise-scale value. ■ Collaborated cross-functionally with sales, growth, and product teams to define roadmaps, drive go-to-market strategies, and expand R&D initiatives, while building strategic alliances with cloud providers, scientific agencies, and ecosystem partners to accelerate regional growth and innovation.
Played a pivotal role as Data & AI Technical Lead in transformation projects, driving end-to-end AI/ML development while partnering with executive stakeholders to translate complex technical concepts into actionable strategies. ■ Coordinated and delivered multiple AI initiatives across Supply Chain, Marketing, HR, and Manufacturing Analytics, leveraging advanced analytics, AI, and NLP to generate actionable insights for strategic decision-making. Selected projects include: ● Supply Chain Analytics: Demand forecasting for retail S&OP processes, inventory optimization, auto-replenishment and transshipment, suggested B2B order prediction ● Marketing Analytics: Marketing mix optimization in retail including assortment, pricing, and promotion optimization ● HR Analytics: NLP CV parsing & smart scoring, OKR quality scoring and alignment, biased language detection in job posts, churn prediction, succession analysis, workforce scheduling ● Manufacturing Analytics: Predictive maintenance, predictive quality, anomaly detection & prediction ■ Designed and implemented MLOps processes covering development, testing, deployment, and monitoring, ensuring scalability, reproducibility, and operational efficiency for seamless production integration. ■ Built reusable, environment-agnostic ML pipelines and abstraction frameworks, enabling consistent deployment through automated CI/CD workflows across on-premise and cloud (Azure, AWS) environments. ■ Mentored and coached data scientists, junior team members, and external training participants for KoçDigital Academy, fostering technical expertise and advancing career development in data science and AI.
2025-2026 Fall&Spring: Foundations and Industrial Applications of Artificial Intelligence
Served as a strategic partner to executive leadership, driving the company-wide data and analytics strategy by leading and closely collaborating with a high-performing team of ~10 data engineers, BI specialists, and data analytics specialists. ■ Designed and managed scalable data warehousing and architecture using SAP BW and SQL Server as core data layers, supporting both self-service reporting and automated, tailored analysis dashboards to feed business intelligence tools. ■ Established standardized data governance practices with a unified data dictionary, defined quality metrics, and implemented an alert mechanism to proactively monitor and resolve data quality issues. ■ Created and executed a cloud migration strategy, conducting feasibility studies and successfully migrating data layers to AWS and Azure, modernizing infrastructure for scalability and cost efficiency. ■ Delivered robust business intelligence solutions (Power BI, SSRS, SAP BW), enabling self-service reporting, real-time dashboards, and enhanced decision-making across all departments. Achievement: IDC Digital Transformation Award 2019 / Logistic Control Tower ■ Led the end-to-end development of retail merchandising software, integrating advanced analytics tools for demand forecasting, financial merchandising planning, stock option planning, and store capacity planning. ■ Applied advanced retail analytics use cases to strengthen the company’s omnichannel retailing strategy, including: ● Demand forecasting ● Assortment optimization ● Store & Warehouse Capacity optimization ● Auto replenishment & transshipment ● Customer segmentation ● Churn prediction ● Campaign analysis ● Pricing & promotion analysis ● Order logistics analysis
■ Analyzed business unit requirements and conducted development processes, including process evaluation, data analysis, and algorithm development, to drive process improvements in Merchandise Planning, Allocation, and Logistics. ■ Collaborated on report development by analyzing business requirements and supporting the creation of reports using SSRS and QlikView. Additionally, contributed to data modeling and developed ETL workflows using stored procedures and SSIS packages, ensuring seamless data transfer aligned with data warehouse architecture. ■ Conducted and participated in data mining, forecasting, and optimization projects to solve complex supply chain challenges. Integrated insights into systems, addressing areas such as: ●Market Basket Analysis: Identified purchasing patterns to enhance cross-selling opportunities. ●Out-of-Stock and Lost Sales Analysis: Minimized inventory gaps and improved sales performance. ●Cluster Analysis: Grouped stores based on performance metrics to guide tailored strategies. ●Demand Forecasting: Predicted future demand trends using statistical and machine learning techniques, enabling proactive inventory and production planning. ●Store Capacity and Packing Optimization & Simulation: Streamlined store operations and logistics. ●Auto Replenishment: Automated stock refills to ensure consistent product availability. ■ Created comprehensive functional and technical documentation to support system enhancements.
■ Spearheaded the development and maintenance of Logistic Vision 3 (LV3), integrating customer-specific requirements by developing web services, custom adaptations, and reporting modules to streamline operations and enhance user experience. ■ Designed and developed .NET-based applications to support key business functions, including: ●Transshipment Management: Optimized cargo handling and routing processes to minimize delays and maximize operational efficiency ● Human Resources Management: Built tools to support employee management across logistics and warehousing operations, improving workforce planning and performance tracking. ■ Designed and implemented end-to-end reporting solutions, including ETL pipelines, datamarts, and .NET-based reporting dashboards, ensuring reliable data processing and enabling data-driven decision-making.