I am a computational scientist - grant solutions architect for the University of Chicago Research Computing Center. I work closely with faculty to identify, develop, and implement computational, data science, and machine learning methods that advance their research. I assist faculty with all aspects of grant writing, focusing on the computational aspects of the their research.I earned a Ph.D. in physics from Indiana University under Steve Girvin and did a postdoc in physics at Georgia Tech under Andy Zangwill. I have published in journals as varied as Physical Review Letters, American Journal of Physics, American Mathematical Monthly, and Tikkun on topics ranging from quantum phase transitions, magnetic thin films, density functional theory, the finite difference time domain method, bias in congressional apportionment, and social justice. I spent many years as a corporate researcher for the AFL-CIO. I have been a community organizer, science teacher, patent analyst, and data scientist.Skills: Supervised Learning, Unsupervised Learning, Data Science, Machine Learning, Deep Learning, Python, SQL, Pandas, NumPy, SciPy, Scikit-learn, Keras, XGBoost, LightGBM, Apache Spark, PySpark, Git, Data Mining, Data Wrangling, Visualization, Data Storytelling, Logistic Regression, Linear Regression, Regularization, LASSO, Ridge, Ensemble Methods, Gradient Boosting, Random Forests, Neural Networks, K-Nearest Neighbors, Support Vector Machines, Gradient Descent, PCA, K-means Clustering, ANOVA, Hypothesis Testing, A/B Testing, Algorithms, Data Structures, Microsoft Office.