lekha ramadasa

MSc in Computer Science (Thesis) with area of interest in machine learning, deep learning, and tensor decomposition techniques

Junior Data Scientist | Tata Consultancy Services | 2018-10 to 2019-06

• Worked on building classification model for telemarketing data to classify whether people purchased the product or not.
• Developed data ingestion, data visualization, data cleaning and imputation, model selection and hyper parameter tuning pipelines.
• Implemented models using SVM, Random Forest and K-means clustering.
• Deployed the model using Flask and performed predictions that gave an F1 score of 0.89. 

Data Analyst | Tata Consultancy Services | 2018-01 to 2018-09

• Worked on collecting data from different sources for bank services feedback.
• Developed data ingestion, data cleaning and preprocessing pipeline for analyzing and processing the collected data.
• The data preprocessing component mainly consisted of missing data imputation techniques and text data preprocessing.

Worked on data visualization for analyzing the processed data and drawing insights from the data to the product owner.

MSc in Computer Science (Thesis) with area of interest in machine learning, deep learning, and tensor decomposition techniques. Currently working on Joint Analysis of relational data using tensor decomposition techniques for efficient utilization of latent factors of coupled data that finds application in recommender system, link prediction system and computer vision.