Chris is a data scientist with a decade of experience split between academic and professional settings. He specializes in creating predictive models to solve unique and interesting problems. He uses his knowledge and expertise to provide data driven guidance that enables businesses to grow and advance. Freelancing allows him to expand his knowledge and work on challenging and unique problems in varied domains.
Developed an app that harnesses the power of ChatGPT to make AI accessible to real estate professionals. This app not only uses ChatGPT to create content but integrates data from other sources to provide richer context.
Created a business to sell data science as a subscription service. This business model is a new way to access and interact with senior talent.
Took an idea from conception through MVP and into production. Marketed and sold the product through relevant industry avenues.
Developed and deployed a model to predict a customers income based on initial credit bureau data. By making the prediction before requiring additional information we reduced friction and churn throughout the underwriting process.
Built cashflow models and forecasting tools to accurately predict customer repayments.
Led the transition to kubernetes from a data science perspective. Orchestrating models into model as code and providing configuration assets for deployment in K8s clusters.
Developed an algorithm to detect broken and defective meters based on usage patterns, saving our clients millions of dollars in lost revenue each year.
Successfully managed multiple projects across multiple clients, from requirements gathering through final product delivery.
Implemented deep learning neural nets to predict customer behavior and automatically identify specific usage characteristics, which saved our clients millions in maintenance costs while increasing customer satisfaction.
Created models to predict price movements in highly liquid commodities, futures, and power markets, which consistently produced returns in excess of 75% annually.
Implemented and maintained all internal reporting for business and trade development, including deploying and managing an internal website which provided on-demand reporting using the R Shiny platform.
Managed financial risks associated with commodities and futures positions held by the firm across all markets and exchanges.
Developed programs and processes to reduce human evaluation of data and quantify subjective analysis.
Worked closely with management to provide analysis and data-driven recommendations for business growth and development.
Developed curriculum for and implemented graduate-level statistical computing course taught to incoming graduate students.
Constructed and taught undergraduate statistics courses focusing on theory and application of traditional statistical techniques and the technologies used to implement them.
Worked in a team environment to define teaching objectives for undergraduate statistics courses.
