Feb 2021 – Jul 2022 · 1 yr 5 mos

Sep 2019 – Feb 2021 · 1 yr 5 mos

Oct 2018 – Aug 2019 · 10 mos · Houston, Texas

• Core member of startup aimed at creating data-science based solutions and provide consulting services.
• Machine learning Models Built:
• Lead Scoring model: Helps Identify new customers by predicting the probability of a non-customer becoming a customer
• Product Association model: A model that aimed at improving up selling by mining product association rules from customer transaction history
• Probability to win: Predicts the probability of an ongoing negotiation being successful based on time spent on different stages.
• Consultant
• Baker Hughes GE
• Worked with the client to identify use cases and fetched requried data from client’s databases.
• Used Text mining, machine learning (supervised and unsupervised) and descriptive analysis to realize use cases and presented solutions to client on a weekly basis.
• Prince International Incorporated
• Performed exploratory analysis and built a customer segmentation model to help identify opportunities for pricing improvements
• Built and deployed dashboards using Power BI for the use of cross-functional teams.

Aug 2018 – Oct 2018 · 2 mos · Sunnyvale, California

• Transform unstructured data in HTML pages into structured data using internal tools, XPath and JavaScript.

Sep 2017 – Dec 2017 · 3 mos

• Teaching assistant for a class of 76 students in topics including E-R & E-E-R modeling, normalization and SQL
• Assisted in creation of a GTFS based dataset and content for term project
• Taught four weekly lab sessions (3 undergrad, 1 graduate) on MS Access and SQL

Jun 2017 – Jan 2018 · 7 mos

• Instrumented a surface grinding machine with five different types of sensors
• Designed the data collection process to measure surface roughness and record sensor data
• Used MATLAB to clean sensor signals and extract features to create a dataset for Machine learning model
• Developed prediction models based on deep learning and random forest using forward feature selection process
• Analyzed the machine learning models to determine the best sensors for surface roughness prediction

Mar 2016 – Sep 2017 · 1 yr 6 mos

• Part of a team involved in the development of the Transit Analysis Software tool, a web application for visualization and analysis of transit agencies in the state of Oregon, USA
• Developed new visualizations, created new databases and enhanced existing functionality of the above application
• Resolved technical issues by leveraging strengths in coding and debugging
• Lead the transition of the web application from the university to Trillium Solutions, Inc., a consultant organization