Charles Rice — Senior Data Scientist

A seasoned professional with a diverse background that seamlessly blends mathematics, machine learning, and extensive programming expertise. Charles Rice holds a Bachelor's degree in Mathematics from Wayne State University in Detroit, Michigan, laying the foundation for a career marked by innovation and technical excellence.

While pursuing graduate studies at Portland State University, Charles delved into the intricate world of machine learning, specializing in areas such as neural networks, reinforcement learning, and genetic algorithms. This academic pursuit translated into practical experience as Charles actively contributed to research projects, showcasing his commitment to staying at the forefront of cutting-edge technologies.

With over 30 years of programming experience, Charles has become a seasoned professional, demonstrating proficiency in a vast array of tools and languages. Charles is well-versed in Python, Pandas, NumPy, spaCy, TensorFlow, Keras, PyTorch, Scikit-Learn, SQL, and various other data science and machine learning libraries. This extensive skill set has been honed through his involvement in projects for renowned companies such as Ford Motor Company, Btrieve, Tektronix, Nike, Xerox, and Hewlett-Packard. Charles has frequently assumed leadership roles, contributing not only technical prowess but also strategic insight to project teams.

The journey into the world of technology began in Charles's teenage years, where he was an active participant in the Detroit Electronic Music and Punk Rock scenes. This creative background is evident in his early ventures, such as building effects pedals for his guitar, programming synthesizers, and engaging in music production with friends. The passion for technology emerged early, as he started programming computers in high school and continued down that path with unwavering enthusiasm.

With a unique blend of mathematical acumen, extensive machine learning expertise, and a rich background in programming and technology, Charles remains at the forefront of innovation, continually pushing the boundaries of what is possible in the realms of data science and machine learning

Data-Centric AI

Data-Centric AI is a paradigm that prioritizes the strategic management and utilization of data to drive intelligent decision-making and enhance overall performance.

By placing data at the core of AI development, organizations can build robust models that adapt, evolve, and continuously improve with each new piece of information.

Data-Centric AI emphasizes the quality of data over the quantity. Rather than simply accumulating vast datasets, this approach prioritizes the collection of relevant, high-quality data that aligns with the specific goals and objectives of the business. This targeted approach not only streamlines the AI training process but also ensures that the resulting models are more accurate and reliable.

Data Science

Data Science encompasses a wide range of topics. I have experience with neural networks, NLP, tabular data, machine learning, data visualization and analysis.

Computer Vision

I have extensive experience with image classifiers and object detection using PyTorch and TensorFlow.