I am a data scientist passionate about building tools for the life sciences. I am experienced in extracting insights from biology datasets of many types. My PhD training was in bioengineering with a focus in microfluidics for high-throughput cell biology applications. Since then, I have gained valuable experience in the biotechnology tools industry, having worked in technology development of several NGS platforms: Berkeley Lights Beacon, 10x Genomics Spatial Transcriptomics (Visium), NanoString Hyb&Seq and CosMx Spatial Molecular Imager. I'm proud to have been an inventor on several patents at each of these companies. Most of all, I have become enamored with making sense of big datasets from high-throughput technologies. To this end, I have pivoted from hybrid experimentalist / computational roles to a dedicated computational career path, as a Data Scientist. I believe that my domain knowledge at the intersection of DNA sequencing, biophysics, statistics and data science, and new technology development gives me unique value in the life sciences tools space. I am always curious and driven to learn new things in this ever-changing field.Skills:• Data analysis, both ad hoc and pipeline development, using Python, R, and MATLAB, most fluent in Python data science stack: numpy, pandas, scipy, scikit-learn, matplotlib, seaborn, plotly; shell scripting• Comfortable with software engineering best practices: Git, PyCharm, VS Code, Azure DevOps ecosystem, object-oriented programming• Well-versed in modern molecular biology methods, especially in NGS workflows: inventor of NGS methods, as demonstrated in multiple patents • Strong background in fluorescence microscopy, optics and image processing using MATLAB, ImageJ, opencv• Effective science communicator adept at tailoring clear communications to audiences of all backgrounds as demonstrated in leading projects, training sessions, customer engagements, and science museum volunteer activity