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Swopnim Ghimire

@swopnimghimire

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Data science research assistant building predictive models and analyzing research datasets.

Nepal

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What I'm looking for

I’m interested in academic research, thesis data analysis, and research support, and I’m adaptable to different research domains and unfamiliar datasets.

My customer churn analysis examined approximately 3,150 telecom customer records through data cleaning, exploratory analysis, and statistical testing. I compared Logistic Regression, Decision Tree, and Random Forest models, with the best-performing Random Forest reaching 94.6% accuracy and 0.987 ROC-AUC.

I developed an Autonomous Credit & Lending Orchestrator for Nepal using XGBoost and SHAP on approximately 50,000 synthetic applicants. I also developed a CNN-based MNIST Digit Recognition Dashboard using Python and Streamlit.

At Kathmandu University, I’m studying for a Bachelor of Data Science, graduating in 2028. I’ve explored transformer-based language modelling through TinyBigGPT and ranked 10th nationally in the final round of the Harvard Health Hackathon.

Experience

Work history, roles, and key accomplishments

Data Science Projects

Self Employed

Feb 2026 - Aug 2026 (6 months)

Conducted customer churn analysis on telecom data, achieving 94.6% accuracy with Random Forest. Developed an autonomous credit and lending orchestrator using XGBoost and SHAP.