I have experience of working on a broad range of life sciences R&D projects in pharmaceutical drug discovery and quantitative systems pharmacology. I also have experience of applying scientific problem-solving skills more broadly to data analysis and data engineering projects across a variety of supply chain, recruitment, agri-tech, and consumer electronics industries.
I am looking for projects that enable me to leverage my scientific problem-solving experience with the application of emerging technologies in data science, particularly modelling, simulation, machine learning and data visualisation.
I provide quantitative systems pharmacology consultancy to pharmaceutical drug discovery projects.
I was responsible for providing data science support to collaborations between IBM Research, the science and technology facilities council, and small/medium-sized enterprise to deliver exploratory data analysis and dashboard tools.
I was responsible for providing mathematical modelling and data analysis support to quantitative systems pharmacology consultancy projects, specifically in the field of immuno-oncology.
Working as part of a small interdisciplinary life sciences team in the Hartree centre, and in collaboration with IBM Research, I was responsible for identifying opportunities in genomics and systems biology where high-performance computing could provide a competitive advantage to UK academic and industry partners.
As a computational biologist at AstraZeneca I gained experience of mathematical modelling of biological systems for pharmaceutical drug discovery. I worked primarily in the oncology disease area and developed quantitative systems pharmacology models in collaboration with high throughput experimental scientists, DMPK modellers, and clinical teams. My work was applied to phase 1 clinical trials to enable dose scheduling and drug efficacy prediction. I was also responsible for managing the outsourcing of systems pharmacology projects and collaborated with third-party organisations in the US, Russia, and Sweden for oncology and cardiovascular research, delivering modelling support to drug development programmes.
In my time between projects, I also enjoy working on a number of Kaggle datasets to develop skills in machine learning. I have built a range of models with application in life sciences and finance. My work is available on my GitHub page: https://github.com/scheckley.