Basel, Basel, Switzerland
I am a Principal Scientist with more than 20 years of experience in pharmaceutical research, analytical chemistry and NMR spectroscopy, combined with hands-on expertise in data science, scientific software development, simulation and laboratory workflow optimization. My work sits at the intersection of scientific expertise, laboratory operations and digital innovation. In parallel with advanced NMR analytics, I design and develop data-driven solutions to improve laboratory efficiency, sample logistics, instrument utilization and operational decision-making. My recent work includes the development of Python-based monitoring applications, discrete-event simulation models for analytical laboratory networks, and constraint-based optimization tools for the deployment of analytical methods across instruments. I have also worked on machine learning applications for scientific research, including crystallization solvent prediction, molecular similarity and analysis of chemical structures. My technical experience includes Python, SQL, SimPy, optimization, machine learning, Streamlit, Power BI, Spotfire, AWS, Docker and CI/CD. I hold an RNCP Level 7 qualification in artificial intelligence and machine learning engineering. I combine deep scientific domain knowledge with data and software engineering to deliver practical solutions for laboratory operations and scientific decision-making.
As a Principal Scientist, I combine advanced NMR analytics with data science, software development, simulation and laboratory workflow optimization. • Develop data-driven solutions to improve analytical laboratory operations, sample logistics and instrument utilization • Design and maintain a discrete-event simulation of the Lab2Lab analytical network using Python and SimPy to estimate sample completion times and evaluate operational scenarios • Develop a constraint-based optimizer to improve the deployment of analytical methods across instruments • Integrate technical and operational constraints, including detector compatibility, mobile phases, column capacity, instrument restrictions, method exclusions and redundancy requirements • Build Python and Streamlit applications for sample monitoring, waiting-time estimation and operational decision support • Create dashboards and analytical tools using Power BI and Spotfire to monitor network performance, turnaround time and workload distribution • Develop and deploy containerized workflows using AWS, Docker, SQL and CI/CD practices • Apply machine learning and molecular representations to scientific projects, including crystallization solvent prediction and molecular similarity analysis • Collaborate with laboratory scientists, automation experts, data scientists and operational stakeholders to translate scientific challenges into practical digital solutions
Novartis – Scientific Operations / Digital Innovation • Developed a discrete-event simulation model of a multi-building analytical laboratory network • Used Python and SimPy to model sample queues, instrument availability, analytical sequences and inter-building transportation • Developed a monitoring application to predict sample completion times and support operational decisions • Integrated laboratory databases and historical operational data using SQL • Contributed to containerization, cloud deployment and CI/CD workflows using Docker and AWS • Worked with data scientists and software developers to adopt production-oriented engineering practices • Applied the acquired capabilities to ongoing Lab2Lab optimization and digitalization activities
• Provided advanced NMR spectroscopy support for small-molecule drug discovery projects • Conducted structure elucidation of metabolites, impurities, natural products and complex pharmaceutical compounds • Developed Python and shell-based automation tools to streamline scientific data processing and laboratory workflows • Designed graphical interfaces and internal tools for analytical scientists • Contributed to the management and optimization of scientific data generated by the analytical research group • Supported the maintenance, troubleshooting and continuous operation of Bruker NMR spectrometers • Collaborated across analytical techniques to resolve complex structural and scientific questions
Setting up a LC-SPE-NMR Bruker system.
Study of dissolution system generating results "out of specifications". Implementation of corrective actions.
Synthesis of cyclodextrin derivatives and analysis by NMR.
Analyst in the raw materials laboratory