Ankit B V S

ML Research Assistant

University of Illinois at Chicago•  April 2020 - September 2020

Prediction of Diabetes from Lumiata Claims Dataset • Streamlined ETL operations on a semi-structured Claims dataset and analyzed the important variables i.e. LOINC, ICD 10 and, CPT codes. • Balanced the data using stratified sampling and predicted the probability of diabetes for patients using SVC model achieving a recall of 89%. Identification of Leader words from any local meaning • Optimized Python script to transform unstructured data from Merriam Webster dictionary to structured format a strong rule-based association. • Modeled a Universal Leader words identifier using Bi-directional LSTM which takes Glove Embedding and POS tags attaining a recall of 96%.

Data Science Intern

AutomizeApps•  May 2020 - August 2020

Twitter Topic Modeling Application [Scikit-learn | CorEx | Microsoft Azure ML Deployment] • Developed an application that applies topic modeling on the tweets of a subject using unsupervised LDA, and semi-supervised CorEx. Obtained 10 different latent topics and their sentiment over 14 weeks. Deployed the model in production using Azure ML deployment. Sentiment Analysis of Product Reviews [Pandas | NLTK | Keras | TensorFlow] • Implemented a rule-based classification and a Deep Learning LSTM model for sentiment analysis of 4 different languages i.e. English, Spanish, German, and French. Restructured the rule-based tool which improved speed and optimized the tool to make it work on any social domain texts. Key Achievement: Reduced time-complexity and achieved accuracy of 92% outperforming Deep learning model by implementing rule-based classifier

Business Analyst

CGI•  June 2016 - June 2016

• Performed statistical analysis of FI and SD data and suggested tangible solutions to stakeholders by visualizing the KPI metrics in Tableau. [Tableau] • Streamlined workflows and applications in SAP business modules deploying the applications using the IBM TWS tool. [Python | SAP ABAP | IBM TWS] • Optimized complex SQL Queries for faster data processing which improved the speed and efficiency of applications by 28% [SQL | Oracle database] Key Achievement: Received “POB Award” for spearheading team of 7 members and managing adhoc requests during challenging time.

University of Illinois at Chicago, Chicago

Data Science, MS•  August 2019 - Present

CourseWork: Statistics for Data Science, Data Mining, Machine Learning Algorithms, Tableau, Advanced Database Management Systems (ADBMS), Deep Learning, Advanced Text Mining, Big Data Analytics, Marketing Analytics, Healthcare Analytics