• Developed and implemented a machine learning model in Python, Keras, and scikit-learn to automate anomaly detection in ION API request patterns, reducing manual review time by 40% and improving detection accuracy by 25%.

• Designed an efficient alert notification algorithm, enhancing the alerting process by 50%.

• Built a chatbot app using React.js and a natural language processing algorithm, increasing user engagement on an automotive website by 20%.

• Integrated Rasa NLU into the chatbot backend with REST API development, cutting initial development costs and reducing development time by two weeks.

• Conducted weekly demos for client feedback, ensuring alignment with project requirements and enhancing client satisfaction.

• Upgraded sensor status software's driver code from C to C++11, ensuring compatibility and robustness for future versions.

• Mentored team members in C++ development and testing with gMock framework, enabling early deployment of the new code base by two weeks.