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Experience

Experience

Work, education, and applied engineering outcomes

My background combines software engineering, data science, machine learning, and backend systems. The common thread is building reliable technical systems with measurable improvements.

Professional work

Work timeline

OOCL

Working Student - Data Analyst

Supporting data process automation and optimization at a global shipping company. Building and maintaining Power BI dashboards and reports, preparing and analyzing operational datasets, and contributing to active digitalization projects.

Working with internal enterprise systems and collaborating across the IT and Data Analytics team in Hamburg.

BISAG-N

Software Developer - Data Science and ML

Designed and deployed ML pipelines for classification, regression, ANN, and CNN workflows using Python, TensorFlow, and scikit-learn.

Improved model prediction accuracy by 18% through feature engineering and reduced manual validation time by about 30% through better preprocessing and evaluation workflows.

Motadata

Software Developer Intern

Built scalable real-time NMS components with Vert.x, Go, ZeroMQ, Kafka, MySQL, and PostgreSQL.

Increased monitoring capacity by 42% to support 1,000+ devices and reduced system latency by about 28% with async event-driven messaging.

tecrave inc.

Software Development Intern

Built a Django CRM portal with REST API integration, optimized MySQL schema design, and documented endpoints with Swagger/OpenAPI.

Reduced client data retrieval time by about 20% and improved onboarding clarity for new developers.

Education

Academic path

M.Sc. Data Science

Technische Universitat Hamburg, 2025 to 2027. Focus areas include advanced machine learning, business and management, and physical systems.

B.Tech Computer Science and Engineering

Ganpat University, 2020 to 2024. Specialized in Big Data and Analytics with coursework across AI, data science, information security, and computer science fundamentals.

Certificates

NVIDIA Fundamentals of Deep Learning, AWS Machine Learning Foundations, AWS Cloud Architecting, Google Data Analytics, IBM Big Data Foundations, and Google Technical Support Fundamentals.

Selected outcomes

What I have shipped

0%Facial recognition accuracy using a Siamese Network.
0+Devices monitored in a real-time NMS platform.
0%Model accuracy improvement through feature engineering.
0%Reduction in manual validation time for ML workflows.