Istanbul, Türkiye
Data & AI leader specializing in advanced analytics and commercial decision intelligence across retail and e-commerce.EU citizen with full work authorization across the European Union, specializing in scaling ML and GenAI solutions, transforming planning functions, and leading cross- functional analytics teams in multinational environments. I have led enterprise-wide transformation initiatives delivering over ₺350M (≈€11M) in revenue growth, 6pp churn reduction, and 25-day lead-time improvements. My experience includes building hybrid forecasting systems achieving 85%+ accuracy across thousands of SKU–store combinations and driving GenAI adoption within organizations of 10,000+ employees. I have headed planning and analytics functions across Turkey, GCC, and EU markets, working with global brands such as Dolce & Gabbana, Versace, Karl Lagerfeld, LC Waikiki, DeFacto and Media Markt. My work consistently sits at the intersection of commercial decision-making, supply chain efficiency, and AI. Currently open to Director / Head-level opportunities in Europe (on-site, hybrid, or remote), where I can help organizations scale data-driven decision intelligence and AI-powered transformation.
• ML-driven Recommender & Ranking Systems Designed and deployed hybrid recommendation and ranking models (collaborative + content-based + business rules) across e-commerce and CRM channels. Replaced external vendor solutions with in-house models, reducing costs by $100K annually while generating ₺350M+ incremental revenue within 6 months. Improved conversion and A2C rates via real-time ranking optimization (CTR, CVR, stock signals). • Customer Analytics & CLTV Modeling Built end-to-end customer intelligence framework including CLTV prediction, churn modeling, and segmentation using ML techniques. Enabled targeted marketing and personalization strategies, resulting in 6pp churn reduction and increased customer engagement. • Forecasting, Supply Chain & Pricing Optimization Developed ML-based forecasting and optimization models (XGBoost, regression, time-series hybrids) across demand planning, allocation, and pricing. Achieved 85% forecast accuracy, reduced lead times by 25 days, and improved stock availability and margin performance. Delivered dynamic pricing use cases impacting profitability. • GenAI & Self-Service Analytics Transformation Led GenAI initiatives including review summarization, size recommendation, and internal copilots, delivering measurable business impact (+3% A2C, –3pp returns). Built self-service BI ecosystem (Power BI, Looker, BigQuery), increasing data accessibility and decision-making speed across functions. • Team Leadership & Scalable Delivery Model Built and managed a 17-person cross-functional data team, defining operating model, hiring, and capability development. Led execution of 10+ concurrent AI/ML projects across CRM, logistics, merchandising, and e-commerce with strong stakeholder alignment. Led advanced analytics & AI-driven commercial optimization initiatives
Established S&OP processes and optimized demand forecasting for $150M business with 400+ stores and 15K SKUs. Implemented RELEX solutions and warehouse capacity planning, improving logistics efficiency. Delivered pricing and assortment optimization models; improved gross margin by 1pp. Managed a team of 30+ across planning, logistics, and analytics.
Managed and mentored demand planning for global brands (D&G, Versace, Karl Lagerfeld) across GCC. Built XGBoost allocation engines with $250K+ monthly benefit. Replaced SlimStock forecasts with ML models (+4pp improvement). Led BI dashboard development via Looker.
Forecasted for 90 stores and 2,000+ SKUs via INVENT Analytics. Achieved 95% availability and reduced aged stock by 5pp. Built centralized stock models used across regions (Greece, Poland). Supported strategic stock control and S&OP meetings.
Developed ML models for pricing, size optimization, forecasts, and scoring. Processed 1B+ data rows per day; improved forecast accuracy by 2pp. Reduced sales loss by 6% and enhanced store turnover.
Created automated top-down forecasting pipelines; accuracy reached 85%. Supported daily replenishment with 56-day forecast horizon. Managed 5-person forecasting team.
Automated return and discount workflows, reducing manual effort by 30%. Designed scalable reporting tools with BI and IT.