SAMPATH KAMALAKANNAN

Client: QPharma. Performed sentiment analysis on key topics to understand public responses (positive, negative, or neutral) for information gathering. Client: CITI RegInsight. Furnished executive leadership team with insights, analytics, reports, and recommendations enabling effective strategic planning. Developed intricate algorithms based on deep-dive statistical analysis and predictive data modeling to deepen relationships and personalize interactions with customers. Analyzed and processed complex data sets using advanced querying, visualization, and analytics tools. Identified, measured, and recommended improvement strategies for KPIs across all business areas.

Client: Biogen Inc., USA. Part of Corporate Compliance Management & Audit (CCMA); Performed monthly audit to understand medical expenses on a drug or vaccine; handled business requests such as updating the logic for flag budget; handled ETL from bronze to silver, silver to gold for data analysis; performed Tableau visualization modifications based on business requests and involved in Databricks. Worked on Enterprise R - Hosted the RStudio in AWS Cloud: Created IQ scripts and installed two servers RStudio Pro (RSP) and RStudio Package Manager (RSPM) in two different EC2 instances; supported activities such as adding packages to RSPM, creating study groups, and monitored log shipping to S3. Worked on R Studio Connect; Created IQ scripts and installed three servers R Studio workbench, R Studio connect, and R Studio package manager and enhanced the enterprise R with R Shiny deployment capabilities.

Client: LTA, NUH, JTC, SGX. Worked on Machine Learning Algorithms for Classification (logistic regression, KNN, SVM, decision tree classifier) for LTA and visualized using Tableau. Implemented deep learning algorithms for Computer Vision (CNN) for NUH. Used Time Series Modelling (RNN, LSTM & Keras) in predicting the Google stock price for SGX. Used Naïve Bayes Algorithm for JTC.

Active member of the team that built ETL from Python / R to PostgreSQL -> Power BI / Tableau / Metabase for a constructed Home Price Prediction dataset. Performed classification and clustering (K-Means and Hierarchical) for a transportation dataset. Worked on ATM transaction data and analyzed global personal vehicles sales. Used predictive analytics to forecast company sales with a 92% percent accuracy rate. Executed descriptive and inferential statistics, including t-test, z-test, and Chi-Square test in R. Performed time series forecasting using ARIMA, Auto ARIMA, RNN LSTM.