Skills
Languages: Python, Java, MATLAB, R, SQL
Scientific stack: NumPy, SciPy, Pandas, Matplotlib, TensorFlow, PyTorch, etc.
Quantum Frameworks: Qiskit, Cirq, Perceval/MerLin; VQE; noise modelling; QRC; hardware-aware optimisation
Software Engineering: PyTest, Git/GitLab CI/CD, Flask, Docker, AWS, microservices, testing & integration, reproducible documentation
Data Analysis: Real-time data pipelines, high-volume sensor data, PostgreSQL, MongoDB, RabbitMQ, experimental benchmarking, statistical validation
Mathematical Foundations: Linear algebra, probability & statistics
Growing in: QEC, QML, Quantum Information
About
Software Engineer and Data Scientist with 5+ years building production-grade Python systems interfacing with physical hardware and sensor networks at Siemens. Experience developing real-time data backends (1,000+ msg/sec), experiment-style data pipelines, and internal tooling used by hardware and measurement teams.
Active in quantum computing through independent projects in VQE benchmarking and photonic quantum machine learning using MerLin. Teaching quantum algorithms to 3,000+ students globally. Interested in transitioning to the quantum industry by applying software engineering rigour to experimentation, algorithms and ML.
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