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Data Scientist with less than a year in Predictive Modeling & Machine Learning.
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Highly motivated Data Scientist with a Master's in Mathematics and over 10 years of teaching experience. Recently transitioned into Data Science after completing the AI/ML Program from The University of Texas at Austin and the Applied Data Science Lab from WorldQuant University. Skilled in machine learning, predictive modeling, data preprocessing, and visualization. Passionate about applying analytical and mathematical expertise to extract actionable insights and solve complex business problems.
The University of Texas at Austin
Post Graduate Program · Artificial Intelligence & Machine Learning
August 1, 2023 – June 30, 2024
HNB Garhwal University, Uttarakhand
M.Sc. · Mathematics
August 1, 2007 – June 30, 2009
HNB Garhwal University, Uttarakhand
B.Sc. · Mathematics
August 1, 2004 – June 30, 2007
WorldQuant University
Applied Data Science Lab
N/A – June 30, 2025
HNB Garhwal University, Uttarakhand
B.Ed.
N/A – Present
Solar Secure Solutions
Data Science Intern
November 1, 2024 – January 1, 2025
India
Various Schools
Mathematics Teacher
January 1, 2010 – April 1, 2020
India
Computer Vision Project (Capstone) – Pneumonia Detection
June 1, 2026 – June 1, 2026
Built a CNN model for pneumonia detection from chest X-rays. Applied preprocessing & augmentation, achieving 82% accuracy.
Unsupervised Learning – Vehicle Segmentation
June 1, 2026 – June 1, 2026
Clustered cars by fuel consumption and features, applying Clustering, SVM, and PCA.
Volatility Forecasting in India (Time Series – GARCH Model)
June 1, 2026 – June 1, 2026
Create a GARCH time series model to predict asset volatility. Pulled stock data through an API, clean and store it in a SQLite database, and build their own API to serve model predictions
Semiconductor Yield Prediction (Feature Engineering & Model Tuning)
June 1, 2026 – June 1, 2026
Built supervised & ensemble models to predict Pass/Fail yields, improving process throughput and reducing costs.
Customer Churn Prediction – Telecom Data (Ensemble Learning)
June 1, 2026 – June 1, 2026
Designed an automated ML workflow to predict customer churn, aiding customer retention strategies.
Cuemath Online Teacher Certification
Cuemath
June 1, 2026 – Present
AI for Everyone
Coursera
June 1, 2026 – Present
CTET
CBSE
June 1, 2026 – Present
Generative AI
Great Lakes Executive Learning & UT Austin
June 1, 2026 – Present
Applied Data Science Lab
WorldQuant University
January 1, 2025 – Present
Artificial Intelligence and Machine Learning
University of Texas at Austin
January 1, 2024 – Present
Cultural Fit Analysis
The candidate shows a strong drive for continuous learning and career transition, evidenced by pursuing multiple certifications and a post-graduate program in AI/ML after a decade in teaching. The academic projects cover a diverse range of data science applications, indicating a broad interest and willingness to tackle different types of problems. The teaching background suggests a structured approach to problem-solving and potentially good mentorship qualities. The candidate's profile aligns well with a learning-oriented and collaborative team culture.
Soft Skills & Operational Fit
The candidate's background as a Mathematics Teacher suggests strong communication, analytical, and problem-solving skills, which are transferable to a data science role. The internship experience indicates an ability to work in a collaborative team environment and contribute to practical data science projects. The transition into data science demonstrates adaptability and a strong learning drive.