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.
• 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 "