Venkateswara Reddy Pochana
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Experience

  1. Master Thesis, Data Science

    | Dow Silicones Deutschland GmbH |

    Led data science research to optimize polymer manufacturing across 10+ critical process checkpoints by running statistical correlation analyses and establishing standardized data workflows across EMEA teams. By training machine learning models on historical batch data to forecast final product properties from raw material inputs, I achieved 90% prediction accuracy—effectively identifying key quality drivers (>70% correlation) and cutting experimental trial iterations in half.

  2. Data Engineer Intern

    | Carl Zeiss AG |

    Built automated data pipelines and analytics solutions for logistics operations. Developed a Python-based document intelligence pipeline using NLP to process 10,000+ freight invoices per month, integrated logistics APIs with Azure Data Factory and Databricks for near real-time shipment tracking, and created Power BI dashboards that improved shipment visibility, enhanced freight analytics, and contributed to a 20% reduction in delivery delays.

  3. Business Intelligence Intern

    | Bosch Rexroth AG |

    Developed a master data management solution with historical data tracking to improve billing accuracy for 2,000+ customers. Built FastAPI services integrating Azure SQL and MongoDB, and automated invoice generation and reporting using Microsoft Power Platform (Power Automate, Power Apps, and Power BI), streamlining business workflows and reducing manual effort.

  4. Project Management Intern, Data Analytics

    | Amazon |

    Built cloud-based data pipelines using AWS S3, Lambda, and Redshift to automate ingestion and processing of 100K+ EMEA food safety compliance records. Developed AWS QuickSight dashboards that centralized compliance analytics, improving reporting efficiency and enabling data-driven operational decisions.

  5. Production Engineer

    | Divya Industries |

    Led data-driven process optimization initiatives that increased manufacturing efficiency by 15% and reduced operating costs by 10%. Integrated laser cladding technology into production workflows, improving component wear resistance and extending product life by 30%.