Mojtaba Karbalaei Email & Phone Number

Hamburg, Hh, De

Hamburg, Germany

Mazandaran, Iran

• Designed and established an integrated SQL-based relational database from decentralized data sources, defined KPIs, and created Power BI dashboards to provide real-time insights, resulting in a 19% performance improvement.• Accelerated data-driven decision-making by implementing interactive, real-time Power BI dashboards powered by SQL queries, reducing report generation time by 90%.• Forecasted future budgets based on historical data and market trends by engineering regression-based financial models using Python, improving budget accuracy by 12%.• Identified new market opportunities by leveraging SQL and Power BI to analyze industry trends and competitor data, resulting in an 11% increase in market share for focused product categories.• Performed churn analysis using Logistic Regression for statistical significance and Random Forest for non-linear feature importance, achieving a 10% reduction in churn through targeted retention strategies.• Conducted price sensitivity analysis using SQL and Power BI to identify cost reduction opportunities, achieving an 8% decrease in costs without impacting customer satisfaction.

Kāshān, Esfahan, Iran

• Developed a Python machine learning model (artificial neural network) to predict product quality, resulting in a 10% reduction in pipe defects.• Established and tracked key performance indicators (KPIs) for the sales team, facilitating a 10% increase in annual sales revenue through the implementation of data-informed strategies and target setting.• Improved departmental performance by 25% through data-driven insights based on SQL.• Conducted feasibility studies for over six projects using COMFAR, based on financial data and market trends, leading to budget allocations exceeding $10 million across projects.

Kāshān, Esfahan, Iran

• Analyzed qualitative data to identify critical-to-quality (CTQ) parameters affecting the final product's quality.• Collaborated with the Production, Quality, and Sales teams to implement PFMEA preparation.• Successfully reduced the scrap iron basket price by up to 10% through the implementation of the DOE approach.• Administered MES, ERP, and SharePoint systems.• Optimized system operations through statistical techniques, resulting in an 8% reduction in Zinc consumption in the process

Master'S Degree, Industrial Engineering

Master'S Degree, Industrial Engineering

Research Project: "Applying a neural network algorithm to predict defects "