Data Analyst Software Developer

Tejas Raghuvanshi

Toronto, ON, Canada, M*Y *A* *.*********@*****.*** +1-647-***-**** LinkedIn GitHub Education

Honours Bachelor of Science, Computer Science

University of Toronto 09/2021 – 05/2025

Awards and Co-Curricular: Howard Ferguson Scholar, Writer [Article] UofT Borderless Club Skills

Languages: Python, R/RStudio, SQL, C/C#/C++, Java, ASP .NET, JavaScript, React, Rest API, Node.js, Django Libraries: Pandas, NumPy, Matplotlib, Plotly dash, Requests, Beautifulsoup, PymuPDF, Google Charts API AI/ML: Open-CV, NLTK, Gensim, Scikit learn, PyTorch Tools: PowerBI, Figma, Excel, Microsoft Azure, SSMS, Unity Work Experience

Software Developer Intern CGI 05/2024 – 08/2024

Honed skills in agile methodologies, with Azure Devops for version control and participation in Sprint cycles

Successfully integrated dashboard for Insurance transaction data in ASP .NET codebase and used SQL Server Management Studio (SSMS) for maintaining views and stored procedures

Designed a webapp workflow UI/UX in Figma and Developed a prototype using JavaScript and Google Charts API Data Analyst Intern PwC 06/2023 – 09/2023

Developed Health IT dashboard in PowerBI to represent Precision and Salesforce revenue

Contributed to Target State report for a cancer hospital with in-depth market research on health tech innovations, case studies of successful implementation, benefits, timeline and operational cost

Prepared an Enterprise Context Diagram for explaining healthcare process workflows in client meetings and researched on key health indicators to consider for medical interventions, available govt. visuals and statistics Machine Learning Intern Cadence Design Systems 05/2023 – 08/2023

Developed text generation NLP model using NLTK and Gensim python libraries, based on Ngram and Word2Vec methods for word prediction. Model was pre-trained on corpus text extracted from datasheets

Successfully automated searching and reading datasheets for circuit instruments. Used Requests and Beautifulsoup libraries for webcrawling and extracted text/images using PymuPDF. Scripts delivered labelled data for 8000+ datasheets in less than 4 hours

Data Science Intern Absolute 05/2022 – 08/2022

Developed image processing scripts using Open-CV library for masking, contour detection, and extracting accurately cropped leaf disease parts. Used to augment image dataset for disease prediction model, improving its accuracy

Developed python scripts to determine sowing/harvest dates for farm coordinates using Pandas, Matplotlib, Earth Engine libraries to process/analyze satellite image data. Built a robust algorithm based on NDVI value variation and adjustment for high cloud cover probabilities, resulting in precise calculation of agricultural timelines Projects

Eedi Correctness Prediction Model 2023

Built ML algorithms (kNN, IRT, Neural Networks) to predict student correctness to diagnostic questions in an online Ed platform. Improved IRT with additional parameters age and guess probability to avoid biases and increase accuracy Unite Social Media App 2022 [GitHub]

Developed a social media app in Java to connect people based on common interests. Provided features like authentication, profile management, group creation, friend search, messaging and reactions Covid19 - Impact on Digital Learning 2021 [Report] Explored digital engagement in 2020 across school districts in the US using Python. Comparison of engagement index with factors like expenditure revealed a digital divide and other interesting correlations Hospital Dashboard, Jaypee Healthcare 2021

Created an IT dashboard using Plotly dash python library and SQL database to create visual representations for daily occupancy census, diagnostics volumes and categorical revenue

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