About Me
Hey! As of early 2026 I’m pursuing my master’s degree at University of Washington, with prior industry experience as a Data Scientist at Dell Technologies, where I built analytics and ML-driven insights for product and business decisions 😊 I’m also a Research Assistant at the eScience Institute, where my current project involves collaborating with astronomical researchers from Rice University and Caltech on open-source scientific data platforms and large-scale datasets.
I’m deeply interested in understanding user behavior through data, especially customer clickstream analysis and how people interact with digital products. I enjoy working on problems around user journeys, engagement, drop-offs, and personalization, and I’m drawn to data science roles focused on product analytics, behavioral modeling, and recommendation or personalization systems.
Alongside this, I’m currently working on a capstone project with Google, applying data and systems thinking to real-world, production-scale problems 💡
Outside of data, I’m curious about marketing, psychology, music, and design 🎧 🎨 I love singing and reading in my free time. I’d be glad to connect through my socials! (on the left 😉)
Hey! As of early 2026 I’m pursuing my master’s degree at University of Washington, with prior industry experience as a Data Scientist at Dell Technologies, where I built analytics and ML-driven insights for product and business decisions 😊 I’m also a Research Assistant at the eScience Institute, where my current project involves collaborating with astronomical researchers from Rice University and Caltech on open-source scientific data platforms and large-scale datasets.
I’m deeply interested in understanding user behavior through data, especially customer clickstream analysis and how people interact with digital products. I enjoy working on problems around user journeys, engagement, drop-offs, and personalization, and I’m drawn to data science roles focused on product analytics, behavioral modeling, and recommendation or personalization systems.
Alongside this, I’m currently working on a capstone project with Google, applying data and systems thinking to real-world, production-scale problems 💡
Outside of data, I’m curious about marketing, psychology, music, and design 🎧 🎨 I love singing and reading in my free time. I’d be glad to connect through my socials! (on the left 😉)
Hey! As of early 2026 I’m pursuing my master’s degree at University of Washington, with prior industry experience as a Data Scientist at Dell Technologies, where I built analytics and ML-driven insights for product and business decisions 😊 I’m also a Research Assistant at the eScience Institute, where my current project involves collaborating with astronomical researchers from Rice University and Caltech on open-source scientific data platforms and large-scale datasets.
I’m deeply interested in understanding user behavior through data, especially customer clickstream analysis and how people interact with digital products. I enjoy working on problems around user journeys, engagement, drop-offs, and personalization, and I’m drawn to data science roles focused on product analytics, behavioral modeling, and recommendation or personalization systems.
Alongside this, I’m currently working on a capstone project with Google, applying data and systems thinking to real-world, production-scale problems 💡
Outside of data, I’m curious about marketing, psychology, music, and design 🎧 🎨 I love singing and reading in my free time. I’d be glad to connect through my socials! (on the left 😉)
Hey! As of early 2026 I’m pursuing my master’s degree at University of Washington, with prior industry experience as a Data Scientist at Dell Technologies, where I built analytics and ML-driven insights for product and business decisions 😊 I’m also a Research Assistant at the eScience Institute, where my current project involves collaborating with astronomical researchers from Rice University and Caltech on open-source scientific data platforms and large-scale datasets.
I’m deeply interested in understanding user behavior through data, especially customer clickstream analysis and how people interact with digital products. I enjoy working on problems around user journeys, engagement, drop-offs, and personalization, and I’m drawn to data science roles focused on product analytics, behavioral modeling, and recommendation or personalization systems.
Alongside this, I’m currently working on a capstone project with Google, applying data and systems thinking to real-world, production-scale problems 💡
Outside of data, I’m curious about marketing, psychology, music, and design 🎧 🎨 I love singing and reading in my free time. I’d be glad to connect through my socials! (on the left 😉)
Skills & Tools
Portfolio
Travel Recommender and Itinerary Generator
A Travel Itinerary generator customised to the user's vacation type, budget and other details. The Itinerary suggests possible places the user would like to visit tailored to the available timings. This project considers only Jaipur, India as the destination city at the moment.
Cross Content Recommender
Cross-content recommendation system that matches book genres to movies using word embeddings and attention mechanisms on 10K+ titles.
Experience
Experience
Experience
Data Science Graduate Research Scholar (SSEC OVRO-LWA Project): Sep'25–Present at eScience Institute, University of Washington
- Developing Python analytics platform for Caltech's 96TB radio astronomy dataset, implementing distributed data processing with Xarray and Zarr for large-scale time series analysis and multi-dimensional data exploration.
- Building interactive visualization and statistical analysis tools using HoloViz for astronomical data mining, collaborating with Caltech and Rice researchers on cloud-based analytics infrastructure via S3 API.
Data Science Intern: Jun'25–Sep'25 at University of Washington, UW IT
- Engineered LSTM forecasting system integrating transactional databases via SQL Server, implementing hierarchical temporal feature engineering to enable multi-year revenue projections, supporting business growth planning and operational efficiency.
Data Scientist 2 (promoted in Mar'24): Aug'22-Aug'24 at Dell Technologies
- Driving experimentation-focused data science initiatives within the Customer Sentiment organization, supporting data-informed product and marketing decisions.
- Collaborating with a team to develop a keyword-based self-serve chatbot for internal stakeholders, aimed at streamlining communication and improving operational efficiency.
- Spearheaded the development of an advanced entity recognition system using SpaCy, resulting in improved accuracy and efficiency within the system.
- Conducting extensive research on Bayesian Statistics as a possible alternative to current practices
Winter SWE Intern: Feb'22-May'22 at Dell Technologies
- As a member of the Information Governance team, played a key role in identifying inconsistencies within Highly Restricted and Restricted data sets through the use of SQL programming, Power BI visualization analysis, and Informatica Data Quality ETL software.
- Conducted deep-dive analysis and data profiling to ensure optimal data quality and accuracy.
Summer SWE Intern: Jun'21-Jul'21 at Dell Technologies
Played a role in the Enterprise Data Governance team by mapping Dell's data catalogue and conducting a lineage gap analysis to identify and address inconsistencies.