Shengnan Li

Associate Product Manager at Supernova Companies

Shengnan Li has worked in various roles in the technology and data science fields since 2014. Shengnan began their career as a Data Analyst at Jinan Construction Tendering & Bidding Agency Co., Ltd. where they constructed formulas to check outliers in bidding prices, calculated bidding scores, and created pivot tables to report scores and top 3 bidders to experts for hundreds of tender projects via Microsoft Excel. Shengnan also tokenized tender documents, removed stop words and punctuations, converted to word vectors, and calculated cosine similarities among tender documents via Python, NLTK, and sklearn, and reported very similar documents to experts for further checks to find possible colluded bidding. Additionally, they developed an Excel macro to auto-load dozens of priced bill of quantities to one sheet and saved hours of manual copy/paste. In 2019, Shengnan Li moved to CCC Intelligent Solutions as a Data Scientist Practicum where they created a recommendation Chatbot to help users select appropriate AWS EC2 instances fitting their use cases to save users’ time, resources, and money. Shengnan also scrapped documentations of 24 different AWS EC2 instance types from Amazon websites via Beautifulsoup and Requests, and plotted word clouds and charts using Tableau to visualize keywords and TFIDF values for each instance to help users better understand and choose instance types. In 2020, Shengnan Li joined both Supernova Technology™ and Basil Labs as an Associate Product Manager and Data Scientist, respectively. At Basil Labs, they helped businesses reduce negative feedbacks and improve sales by mining 100K+ customer reviews extracted from Google Maps. Shengnan removed HTML tags and stop words from reviews, expanded contractions, and tokenized and lemmatized words via BeautifulSoup, spaCy, and Contractions libraries. Shengnan also trained Topic Classification and Sentiment Analysis models using Python and fastText to estimate topics and sentiment scores for unlabelled reviews, and used cross-validation to evaluate model performance and got 89% predictive accuracy on test datasets.

Shengnan Li obtained a Bachelor's degree in Applied Mathematics from Ocean University of China between 2010 and 2014. Shengnan then obtained a Master of Science in Data Science from the Illinois Institute of Technology between 2018 and 2019. In addition, they have obtained a Triplebyte Certified Data Scientist certification from Triplebyte in August 2020, as well as several certifications from Coursera, including Data Structures and Performance, Object Oriented Programming in Java, Object Oriented Programming in Java Specialization, Java Programming: Arrays, Lists, and Structured Data, and Java Programming: Solving Problems with Software (with Honors).

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