

- Location
- Vancouver, British Columbia, Canada
- Bio
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I am a student at the University of British Columbia studying International Economics with a minor in Data Science. My interests lie in exploring how data can be applied across industries to uncover insights, improve decision-making, and create meaningful impact.
I have gained experience working with data through both professional and academic projects. At Ubineer, I helped design natural language processing tools that allowed a proprietary language model to parse complex financial filings and extract thousands of key data points for investment analysis. In academic work, I applied econometric techniques to financial market data and built predictive models in health economics, which enhanced my ability to clean, process, and analyze large datasets.
I bring a strong foundation in Python, R, and Stata, combined with skills in predictive modeling, regression analysis, and machine learning. Beyond technical expertise, I am passionate about connecting data-driven results with real-world applications and communicating insights clearly to different audiences.
- Resume
- Yash_Dhaundiyal_Resume.pdf
- Portals
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Vancouver, British Columbia, Canada
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- Categories
- Competitive analysis Data science Economics Financial modeling Market research
Skills
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Latest feedback
Achievements



Recent projects
Work experience
NLP Research Assistant
Ubineer
Toronto, Ontario, Canada
February 2025 - May 2025
- Designed and implemented NLP chunking patterns using NLTK to help a proprietary LLM accurately parse financial documents, enabling structured data extraction for KPI prediction.
- Focused on high-quality data collection and pattern validation to support AI-driven investment analysis, streamlining the capture of up to 3,000 data and text elements per company filing.
Finance Director & Director of Corporate Relations
UBC Baja SAE
Vancouver, British Columbia, Canada
August 2024 - Current
- Spearheading a $90,000+ annual fundraising campaign, optimizing resource allocation for engineering projects and implementing cost forecasting tools, streamlining budgeting processes to improve financial planning.
- Building relationships with sponsors leading to an increase of 25% in annual funding and established a bi-monthly alumni newsletter that reaches 200+ recipients, generating fresh sponsorship leads and fostering long-term partnerships.
Vice President of Student Life
Vancouver School of Economics Undergraduate Society
Vancouver, British Columbia, Canada
May 2024 - Current
- Conceptualize and execute wellness programs aimed at improving campus community engagement and building collaborative initiatives with faculty, bridging gaps between academic and social activities for 1,000+ students.
Finance Associate
Tasco International Co., Ltd
Bangkok, Bangkok, Thailand
June 2021 - July 2021
- Conducted thorough market research to optimize resource allocation strategies, achieving a 15% improvement in financial forecasting accuracy and delivered data-driven reports to senior management, simplifying complex insights for informed investment decisions.
Education
Bachelor of international economics (bie), International Economics
The University of British Columbia
September 2023 - May 2027
High School Diploma, International Baccalaureate Diploma
KIS International School
August 2019 - June 2023
Personal projects
Short-Term Reversal and Efficiency in Polymarket Price Data
October 2024 - December 2024
https://github.com/Mr-Slope/Polymarket-Autocorrelation/blob/main/Polymarket_Autocorrelation_James_Fazeli_Sinaki_Yash_Dhaundiyal.ipynb- Analyzed time-series financial data and PACF models using Python to process large datasets, calculate lagged correlations, and visualized trends to identify patterns in prediction markets.
- Optimized code to ensure accurate insights through comprehensive data cleaning and validation techniques; used Facebook’s BART to categorize market prediction questions, improving dataset usability.
Predicting the Presence of Heart Disease
October 2023 - December 2023
https://github.com/Mr-Slope/DSCI-100_Group_Project/blob/main/group_report.ipynb- Processed and cleaned raw heart disease datasets using R and normalized features to ensure data quality and consistency for machine learning applications.
- Developed predictive models and used stratified sampling to maintain data distribution.