During my role as a Data Scientist at DataSolutions Inc., I led several NLP projects, allowing me to manage the project lifecycle hands-on. One particularly valuable experience was when our team implemented a chatbot to improve customer interaction.
The project began with a clear Problem Definition - creating a chatbot to handle high-volume, low-complexity customer queries. I directed the team during the Data Acquisition phase to gather and preprocess thousands of customer interactions. During the Modelling phase, I utilized Python's NLTK and SpaCy libraries to train a model based on our collected data. We then deployed the model and constantly monitored and optimized its performance based on customer interactions and feedback.
The chatbot was able to handle 30% of the total customer queries, proving instrumental in reducing human workload and increasing customer satisfaction.