Professional Summary

Graduated in May 2025 with a 3.88 GPA

Recently completed my Master’s in Business Analytics at Carnegie Mellon University’s Tepper School of Business—a program that blends advanced analytics with strategic business problem-solving. From machine learning to AI-driven financial modelling, my time at Tepper has equipped me with the tools to turn complex data into clear, actionable insights that drive real-world impact.

Key Courses:

Graduated in August 2023 with a 3.24 CGPA and minor in Data Science

I earned my Bachelor’s degree in Mechatronics Engineering from Manipal Institute of Technology, where I graduated in the top 10% of my class with a strong focus on robotics, automation, and data science. Alongside my technical coursework, I actively led student initiatives—serving as President of the Photography Club and contributing to community-driven efforts through IE Mechatronics and the Mudra NGO. This foundation gave me a multidisciplinary lens and sparked my passion for data-driven problem-solving.

Collaborated with Raymond James on a capstone project to enhance Financial Advisor-client engagement using data science.

Developed time series models to track client progress toward long-term goals like education and retirement.

Applied clustering techniques to benchmark Financial Advisors and identify areas for strategic improvement.

Built interactive dashboards using Tableau to deliver clear, actionable insights to advisors.

Utilized Python and AWS to develop scalable, efficient analytics pipelines.

Translated complex financial data into user-friendly visualizations aligned with business goals.

Gained hands-on experience aligning technical solutions with strategic financial decision-making.

Led a team to design data-driven marketing materials, enhancing proposal strategies for insurance clients.

Built an AI-powered email classification tool to automate data extraction for BFSI clients, improving response time and accuracy.

Applied NLP and machine learning techniques to categorize client queries, streamlining customer service processes.

Secured leadership approval for automation initiatives through data-backed performance insights.

Leveraged Microsoft Power BI and Power Platform tools to create dashboards and optimize reporting workflows.

Contributed to operational efficiency and strategic decision-making through intelligent automation solutions.

Conducted feasibility analysis for integrating new data sources, collaborating closely with senior management.

Designed and implemented an automated data validation pipeline, reducing manual processing time by 80%.

Utilized generative AI and statistical modeling to resolve data inconsistencies across large datasets.

Trained four interns in SQL, data quality frameworks, and operational best practices, fostering a collaborative team environment.

Worked with tools such as Apache, AWS, Snowflake, Python, Tableau, and Alteryx to support robust data operations.

Contributed to high-impact projects that supported strategic decision-making across Bain’s data infrastructure.

Served as a Data Science Intern, contributing to the development of data-driven solutions.

Engaged in projects that enhanced analytical capabilities and supported business decision-making.

Collaborated with cross-functional teams to apply data science methodologies to real-world problems.

Gained hands-on experience in data analysis, modeling, and visualization tools.