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Data Science with less than a year in Machine Learning, Time-series Modeling, and Explainable AI.
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Assessing your cultural and operational fit
M.Sc. Data Science student at VIT with a background in full-stack Java development and hands-on experience in machine learning, time-series modeling, and explainable AI. Completed research projects involving LSTM-based sequential prediction and a six-model ML pipeline with SHAP explainability on real-world ICU data (MIMIC-IV, 94,000+ records). Familiar with Reinforcement Learning concepts including Q-learning and policy/value functions. Eager to contribute to intelligent model development for real-world transport and control system applications at Volvo Group.
Vellore Institute of Technology (VIT)
M.Sc. · Data Science
August 1, 2025 – Present
Asia Pacific University (APU)
B.Sc. · Information Technology
August 1, 2021 – June 30, 2024
Cell Pay Private Limited
Junior Java Developer
March 1, 2024 – August 1, 2024
Kathmandu, Bagmati Zone, Nepal
F1 Soft International
Software Engineer Intern
April 1, 2023 – July 1, 2023
Lalitpur, Bagmati Zone, Nepal
Explainable ML for Early Prediction of Acute Kidney Injury (AKI) Using ICU EHR Data
July 1, 2025 – Present
Built a six-model ML pipeline (Logistic Regression, Random Forest, XGBoost, LSTM, etc.) on MIMIC-IV ICU data (94,444 records) for AKI onset prediction — a sequential decision-making problem over time-series clinical signals. Engineered creatinine-based time-series features aligned with KDIGO staging criteria; resolved critical data pipeline issues involving NULL hadm_id joins and narrow time windows. Implemented SHAP-based explainability for model interpretability; produced full HTML reports with multi-model performance comparisons.
Anomaly Detection in Banking Sector Using CPI Data
July 1, 2025 – Present
Developed time-series anomaly detection models using ARIMA and SREMA to identify irregular patterns in financial/macroeconomic data — applicable to sequential monitoring in real-world systems. Performed EDA, feature engineering, and comparative model evaluation; presented results with visualizations.
ICU Length of Stay Prediction (MIMIC-IV)
July 1, 2025 – Present
Built multi-model regression pipeline on 94,444+ ICU records; compared 5+ ML algorithms for predictive performance on time-dependent patient outcome data. Delivered full Jupyter notebooks and HTML reports with cross-validation, confusion matrices, and feature importance analysis.
Core Java Specialization
Coursera
July 1, 2023 – Present
Introduction to Cloud Computing
Coursera
April 1, 2023 – Present
Introduction to Big Data
Coursera
May 1, 2021 – Present
Cultural Fit Analysis
The candidate's background includes both academic data science projects and professional experience in Java development. While the data science projects align well with the target role, the professional experience is primarily in Java, which is not directly relevant to a pure Data Science role. This suggests a potential pivot in career focus. The academic projects show a strong interest in data science, but the lack of industry experience in this specific domain might require additional mentorship and integration into a data science-focused team culture. The candidate's current enrollment in a Master's program indicates a commitment to continuous learning.
Soft Skills & Operational Fit
The candidate demonstrates an ability to work in teams (Junior Java Developer role) and follow Agile processes. Project descriptions indicate a structured approach to problem-solving, including data pipeline issues and comparative model evaluation. The academic nature of most data science projects suggests a strong theoretical foundation and research-oriented mindset.