A data scientist with a background in Python, SQL, machine learning, artificial intelligence, hypothesis testing, and natural language processing, Muneeb Chawla, PhD, serves as an artificial intelligence and machine learning engineer at Auto Profit Masters. Since joining the company in the summer of 2020, Muneeb Chawla has developed deep learning models to predict vehicle repairs, customer churn, and the likelihood of customers responding to marketing messages. He has also built a deep learning model to identify part vendor invoices for automated processing for accounting.

Muneeb Chawla previously worked as a data scientist at CACI International Inc., where he created an XGBoost model to predict aviation delays using METAR weather data. The model proved accurate to within 20 minutes of actual delays. He also built a predictive model that relied on Google Trends data to forecast illicit drug use and state crime rates, attracting the Drug Enforcement Administration to the company’s software tool suite. Other models that Dr. Chawla has built have helped companies detect fraud, predict employee turnover and the cost of this turnover, and compute return on investment for human resource programs.

A resident of Centennial, Colorado, Muneeb Chawla earned his BS in electrical engineering from the University of Colorado before moving on to complete his MS in the same specialty from the same institution. He earned his PhD in engineering from the University of Denver. His competencies in engineering encompass algorithm development, digital signal processing, field-programmable gate array, and RF design.