Diwakar Kuppusamy

• Completed a Master’s thesis at BMW Group focused on data-driven packaging cost optimization. • Built and validated an ML model using XGBoost to predict packaging costs with real data. • Developed and optimized data pipelines utilizing AWS Glue, Athena, and PySpark. • Created dashboards to facilitate data-driven business decisions, enhancing operational efficiency.

Detected and corrected critical anomalies in large-scale pricing datasets, ensuring accuracy across thousands of records. Designed and implemented a unified master database to consolidate and standardize data from multiple sources. Performed long-term cost trend analyses to support business forecasting. Developed and refined interactive dashboards to visualize corrected data and provide actionable insights. Built and tested ETL workflows to ensure production readiness and reliable data integration

Designed & implemented scalable data architectures, improving data classification and injection efficiency by 30%, ensuring seamless integration across business processes. Spearheaded automation initiatives for diverse file types (CSV, JSON, XML), reducing manual interventions and increasing pipeline reliability. Leveraged Vertex AI & Python to optimize data injection processes, boosting both performance and data quality. Mentored junior team members in data engineering fundamentals, strengthening t

I am currently pursuing a Master of Science in Business Intelligence and Data Science at the International School of Management in Munich. This rigorous program provides me with a deep understanding of data analytics, machine learning, and strategic decision-making. Through a blend of theoretical k