Education
- 2022 - 2023
-
2013 - 2017
Anna University, Chennai
B.E Mechanical Engineering
Experience
-
2023 - Present
University at Buffalo
Research Assistant (Data Science)
• Performed in-depth analysis of wildfire data totaling approximately 5 GB. Merged information from diverse
tables to identify counties most impacted, leveraging multiple variables for a comprehensive assessment -
2023 - Present
Department of Energy University Sprint
Data Scientist, The Opportunity Project
• Collaborating with the U.S Department of Energy and the local authorities to develop a first ever two-way
communication application, enhancing public-authority interaction and transparency
• Conducted in-depth user-research interviews with emergency managers and a leader from the Red Cross, uncovering
critical pain points and challenges faced during emergency response efforts; insights directly influenced product
roadmap and feature development.
• Created an interactive tableau dashboard for the emergency managers to view the public’s needs, and conducted
analysis using tableau on power outage data. -
2023 - 2023
RadicalX, New York
Artificial Intelligence Engineer Intern
• Behavioral analysis: Spearheaded the creation of the startup\’s inaugural fraud detection deep learning model,
achieving an impressive 90% validation accuracy. Deployed the model in AWS SageMaker by utilizing AWS ECR to push
the Docker image and create an endpoint from it.
• Developed an AI manager using the Llama-2 7B model within the Langchain framework, replacing the paid OpenAI API
approach -
2019 - 2022
Tata Consultancy Services, Bengaluru
Data Scientist
• Anomaly detection: Developed and deployed an anamoly detection model to detect abnormal vibrational signal using
autoencoder to encode the statistical properties and Kmeans to group signals
• Reliability analysis: Successfully developed a proof-of-concept project involving the reproduction of a statistical model
for the client, leading to the project being awarded to TCS
o Consulted with a subject matter expert from engineering team and developed a rank regression model that matches
the output of commercially available software for estimating machine reliability, resulting in a 60% reduction in costs
associated with reliability estimation
• Predictive analytics: Saved 20% in the cost involved in predicting a network failure for the client
o Integrated data from multiple tables in Azure SQL Database using SQL, conducted data analysis, engineered new
features, and developed a machine learning model to predict network failure on datasets exceeding 5 million records
using azure databricks and effectively communicated analysis outcomes to the client using Tableau by crafting engaging
data-driven narrative -
2018 - 2018
LearnKart Technology, Bengaluru, KA
Research Analyst
• Customer Churn: Led a comprehensive customer churn analysis initiative for an online course, employing data-driven
strategies to boost customer retention