My career sits where data science meets business strategy: not only building models, but asking the right questions, shaping outcomes, and turning analysis into decisions. I thrive on creating scalable solutions that improve processes, inform strategy, and unlock value across teams.
Curiosity, innovation, creativity, and adaptability define how I work. Curiosity pushes me to explore unfamiliar domains, question assumptions, and dig deeper into data until the underlying story becomes clear. Innovation drives me to design scalable, practical solutions building systems and workflows that don’t just solve today’s problem but create long-term value. Creativity allows me to transform complex analyses into compelling insights that stakeholders can act on, while adaptability enables me to navigate evolving priorities, learn new tools quickly, and collaborate effectively across technical and business teams.
English, Hindi, Punjabi
Power BI, Tableau
Python, SQL
Talend, MS SQL, Snowflake
NLP, Machine Learning, Deep Learning
AWS, Sagemaker, Git, Jira
Traveling, Photography, Teaching
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2025 - Present
Working with the Insights and Analytics team on financial data.
2024 - 2025
Worked as an Analyst with the business part of the data team in one of the largest data-sharing programs for aviation.
2021 - 2022
Provided data-based end-to-end IT solutions to industrial companies.
Research on early-stage Alzheimer's detection by utilizing original NIfTI files rather than traditional image files. We curated a unique dataset from raw MRI scans and applied advanced deep learning techniques to identify early biomarkers of Alzheimer's.
The TTC Bus Delay Analytics project transforms over 12 years of raw TTC delay data into an interactive map and dashboard that reveals where, when, and why delays occur across Toronto's transit network. By processing more than 1.3 million records—spanning bus, streetcar, subway, and LRT—the application enables commuters, planners, and advocates to explore delay patterns by route, ward, neighbourhood, and individual stop. Through spatial joins, natural language processing for geocoding, and temporal aggregations, the platform makes complex transit performance data accessible and actionable.
Classifies Wikipedia articles into 200+ categories with 88% accuracy using LSTM.
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Generative AI for resume analysis and ATS feedback.
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Analyzes survey data of data professionals using Power BI.
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