Biography

J Montgomery Maxwell is currently a data scientist with at The University of Chicago’s Center for Translational Data Science (CTDS). He has a M.S. in Applied Mathematics and Engineering Sciences from Northwestern University, and a B.S. in Mathematics and a B.A. in Philosophy from DePaul University. He is interested in the application of data science and artificial intelligence to economics, finance, global affairs, and public policy.

Services

  • Consulting

    I can provide you and your business the expertise you need to leverage the power of your business’s data and to utilize AI to strategically address your business needs.

  • Education

    I’m available for coaching individuals and small groups in mathematics, statistics, data science, and machine learning. Available for virtual sessions or in person sessions in the Chicagoland Area.

Current & Previous Projects

Stochastic Methods

Coming Soon

Coming Soon

Mixed Datatype Clustering

Work Experience

Data Science, Sr. Analyst - Center for Translational Data ScienceChicago

  • Collaborate with stakeholders and external partners to identify opportunities for leveraging both internal company data and third-party data to effectively drive research developments

  • Utilized biomedical, economic, and survey data, to develop machine learning models for predicting trends in public health and patient healthcare outcomes

  • Developed data engineering and machine learning pipelines for automated ETL processes and model deployment

  • Automated reporting workflows for product and user analytics, resulting in efficient delivery of reports within strict timelines, yielding annual time savings of over 100 work hours

Languages & Technology

Python (Pandas, Numpy, Seaborn, Plotly, Matplotlib, Scikit-Learn, and TensforFlow), R, SQL, Jupyter, Github, Docker, Argo, Nextflow, and Kubeflow

Data Science Consulting - Statistics Without Borders

  • Consulted on methodology for standard of living surveys for in international conflict zones

  • Analyzed the clustering methodology used on survey responses from residents of South Sudan and Burkina Faso

Data Science Research Intern - Center for Deep Learning

  • Collaborated in creating a data science pipeline for feature engineering, model training, model deployment for IoT data streams

  • Automated feature engineering and data cleaning processes in the data science pipeline

Technical Strengths

Data Science & Machine Learning

Statistics, Data Cleaning, Data Visualization, Data Engineering, Regression, Random Forests, Unsupervised Learning, and Deep Learning

Contact

Please reach out to me if you have any questions regarding work opportunities or my education and consulting services.