Tell me about a time when you had to use creativity and innovation to solve a challenging problem in your previous role as an Applied Scientist. What was the problem and how did you approach it? What was the final outcome?
Introduction:
As an Applied Scientist at Amazon, I have come across various challenging problems that required innovative and creative solutions. One such instance was when I was tasked to develop a machine learning model that would help enhance customer experience on the Amazon website. The Problem:
The problem I faced was that our existing customer feedback system was not efficient in capturing the sentiments and emotions of customers. The system used traditional surveys and feedback forms which resulted in low response rates and often failed to capture the exact issues faced by the customers. This affected the overall customer experience on the website, which was a matter of concern for the organization.The Approach:
To tackle the problem, I took an innovative approach and utilized Natural Language Processing techniques to develop a sentiment analysis model. The model was trained on customer reviews and feedback data collected from various sources including social media, review websites, and customer support chats. The model was designed to identify and categorize different emotions and sentiments of customers based on the language used in their feedback.The Outcome:
The final outcome was very positive. The sentiment analysis model helped to identify the pain points of customers more accurately and efficiently. The model provided insights on the most common issues faced by customers, enabling Amazon to take prompt action to resolve the issues. This resulted in a significant improvement in customer satisfaction and a substantial increase in the response rate of the feedback system. As a result, the model was implemented globally, and the approach was recognized and awarded by Amazon.References: