Jul 2023 – Sep 2025 · 2 yrs 2 mos · Miami-Fort Lauderdale Area

Aug 2022 – Jul 2023 · 11 mos · Miami-Fort Lauderdale Area

Aug 2020 – Aug 2022 · 2 yrs · Singapore

• Identified customer share of wallet utilizing internal & external datasets for revenue using statistical Mann-Kendall test resulting in segmentation of customers for sales enablement team
• Analyzed publically available WHO clinical trials data to get insights about regions & primary sponsors for active trials being conducted which aided in planning vaccine logistics
• Involved in cost-saving & productivity optimization opportunities for a medical device manufacturer by performing analysis focused on demand size, inventory optimization & order size resulting in a reduction in storage space
• Identified as-is for a global auto company by scanning and drafting all transport modes on a supply chain flow map which was further used for transport mode optimization

Jan 2020 – Jul 2020 · 6 mos · Singapore

• Developed a model for company name deduplication using NLP and XGBoost algorithm to generate potential leads for different countries resulting in improved accuracy compared to previous model from 60% to 72%
• Refined an NLP based company name grouping algorithm by improving its speed and accuracy
• Utilized named entity recognition along with parallel processing in python to improve the performance of the code
• Involved in customer segmentation efforts to label customers from international markets based on their shipping profile
• Applied statistical techniques to categorize customers in different segments which helped business understand the profile of customers before launching a new campaign website
• Developed a supervised and an unsupervised predictive machine learning model using XGBoost and DBSCAN clustering algorithms to perform customer churn analysis
• Prepared a tableau dashboard to visualize the various features from different data sources which are likely to affect the churn probability of a customer

Apr 2018 – Jun 2019 · 1 yr 2 mos

• Worked in the Data Governance team of a US financial services corporation to perform the root cause analysis of the anomalies detected in the key metrics of the variables
• Collaborated with Decision Science Modeling and Strategy teams to understand the cause of variance in the variables used by models
• Refined a key metric being used to measure comment quality by developing an NLP based model to parse user comments given by the analysts on the anomalies in the data quality portal and assign a score to them on how well they define the issue detected
• Integrated two portals of data anomaly detection by creating a web application in Python as part of POC demonstration to senior leadership
• Reduced the effort of Implementation team by automating the manual process by designing a VBA based user form to get input from Decision Science Modeling and Strategy teams and implement an application on a single click

Nov 2016 – Apr 2018 · 1 yr 5 mos

• Created a quotes prioritization logic for a US Logistics client to determine a probability score of conversion of quotes to orders
• Developed agent scorecards to track various KPIs for the agents for a US LTL(Less than Truck Load) client.
• As a part of Analytics team for a UK Insurance client, converted a prioritization score-based model originally in SAS into a VBA tool as per client's request

May 2016 – Jul 2016 · 2 mos · Shimla, Himachal Pradesh, India

• Worked as an intern on-site to understand the overall functioning of hydro electric power plant for electricity generation & transmission

Jun 2015 – Jul 2015 · 1 mo · Chandigarh

• Build an RFID based tag using Embedded C