Glen Ferguson Ph.D.'s Linkedin Analytics

As a data science senior leader with a proven career progression in the health care and wellness space, I offer extensive experience in machine learning, data infrastructure & analytics, data engineering, ML, AI, scientific computational modeling, software development, IT services, and consulting. Having worked in the data science field from its infancy, I’ve been fortunate to witness its rapid growth and evolution from the front lines. My career in data science has culminated in my most recent appointment to Assistant Director of Data Science at a leading CRO’s Advanced Analytics Center of Excellence. In that capacity, I spearhead the development of customized solutions to advance pharmaceutical and biotechnology companies’ successes, particularly in terms of recruitment and enrollment for clinical trials. My immediate priorities are to scale the data science function and capture a several-fold increase in opportunities, changes that would facilitate billions in additional revenue. I also bring to the table a storied history in health care, including as a faculty member at Albert Einstein College of Medicine, as a data science grant manager at the Michael J. Fox Foundation, as a consultant at a health care payor, and in consulting and/or director capacities at multiple wellness companies. As prolific author Robert Heinlein put it, “specialization is for insects;” mine is a diverse skill set that has proven invaluable across multiple fields and teams, time and again, including in these ways: – Leveraging AI & ML to drive operational efficiency, increase precision, improve scale across millions of data points, and solve complex, multidimensional problems. – Significantly increasing the velocity of the development cycle by designing a CI/CD and Infrastructure as a Code system. – Leading teams in building high-value systems to recognize data drift and automatically retrain ML models at certain thresholds. – Drawing on expertise in statistical modeling, visualization, and storytelling to convey complex results in a compelling and easily accessible way. Technical Tools: Python (scipy, numpy, pandas, dask, modin, scikit-learn, bayesian optimization, scrapy, optuna, hyperopt, statsmodels, keras, tensorflow, requests, selenium, PySpark, matplotlib, NLTK, spaCy, Seaborn, Hugging Face), SQL, NoSQL, Docker, CircleCI, MLFlow, Ray, Deep Learning, Decision Tree, Random Forests, Regression Models, Boosting (XGBoost, LightGBM, Catboost), Clustering, Naïve Bayes, SVM, Time-series Analysis, KNN, NLP, and Computer Vision