Calla Boyer

Hi, I’m Calla!

I’m an engineer-scientist and writer working at the intersection of biotech and data science. I’ve spent the last seven years developing processes, analytical methods, and data infrastructure across a wide range of modalities like proteins, mRNA, LNPs, viral vectors, microparticles, and polymers. Along the way, I’ve become the go-to expert for PAT, chromatography, and AI/ML integration in process and analytical workflows.

I work with Python, R, and SQL to analyze data, build ML models, and support internal tool development. I’ve used libraries like pandas, matplotlib, and ggplot2 to clean and visualize data, applied pytorch and scikit-learn to implement unsupervised and supervised learning techniques, and led the development of ETL pipelines and dashboards that make experimental data easier to access and interpret. I’m always learning and expanding my skill set, with a focus on applied data science that complements my biotech development background.

My formal training includes a BS in chemical engineering (with minors in biomedical engineering and English) from Penn State and an MS in microbiology and cell science from the University of Florida. I love to learn, so I’m currently completing a professional certificate in data science with a machine learning concentration from Harvard.

I think data science is most powerful when you pair it with domain expertise and clear communication. Thus far, I’ve spent my career not just developing models and methods, but also building the narratives around how I present my findings and where we go next. My writing background has given me a propensity for data interpretability for more effective decision making—each dataset has a story, and it’s my job to tell it. In fact, I believe in the benefits of training engineers in the humanities and arts so much, that I’ve spoken about at TEDx and SWE conferences.

But, enough about me. Let’s talk about algorithmic learning theory, cross-functional storytelling in the drug development process, and the elegance of a well-tuned gradient on an HPLC!

Sincerely,

Calla