Data Analyst (Graduate) — MSc Data Analytics, Dublin City University 📍 Dublin, Ireland | 🇮🇪 Eligible to Work in Ireland | 🟢 Available Immediately Turning data into actionable insights through Python, SQL, and Machine Learning.
📧 durgaprasadnarsing1728@gmail.com | 🔗 linkedin.com/in/durga-prasad-narsing | 💻 github.com/D-Durga1728
I'm an MSc Data Analytics student at DCU (First Class with Distinction, CGPA 8.30, B.Tech Computer Science & Data Science) who solves real data problems end-to-end — from a memory bottleneck on an 82-million-row dataset to a deployed clinical risk model with fairness auditing. I work in Python, R, SQL, Power BI, and Tableau, and I'm self-directed: every project below was scoped, built, and shipped by me (team projects say so explicitly).
Currently on Stamp 2 (DCU student visa) — eligible to work part-time now, full-time unrestricted from September 2026 via Stamp 1G on MSc completion.
Programming & Analytics: Python (Pandas, NumPy, scikit-learn, XGBoost, Plotly), R, SQL, PostgreSQL BI & Visualisation: Tableau, Power BI, Plotly (animated/interactive), Excel (Advanced) ML & Stats: Classification, regression, Random Forest, XGBoost, cross-validation, hypothesis/A-B testing, feature engineering, model calibration, fairness auditing Deployment: Django, Flask, Streamlit, Git/GitHub Actively learning: React, MCP (Model Context Protocol) & agentic AI workflows, cloud data engineering
Solo — MSc Practicum, DCU · Supervisors: Dr Martin Crane, Dr Tai Tan Mai A 220,218-case clinical dataset had no Long COVID follow-up labels, so instead of overclaiming, I reframed the target honestly as a mortality proxy. Benchmarked a calibrated Logistic Regression (test AUC 0.888) against Random Forest, Gradient Boosting, XGBoost, and Stacking — DeLong testing showed none beat it, so I deployed the interpretable model. Added fairness auditing across age/sex/comorbidity (cut TPR disparity from 0.60 to 0.045) and shipped a live Streamlit risk calculator.
Team Project, 4 members (modelling & reporting role) — DCU CA683 Data Mining Merged 3 open Irish datasets (24 weather stations, EirGrid grid data, SEM wholesale prices) into one unified hourly series. Our Random Forest model reached R² 0.975 on demand and R² 0.972 on price (MAE 6.13 EUR/MWhe), confirmed with 5-fold cross-validation.
Solo — DCU CSC1143 Data Visualisation
An 82-million-row, 31 GB dataset crashed every local load attempt. I rebuilt the ingestion using chunk-based Pandas processing into a working 3,569,724-row set, engineered a daysBeforeFlight feature, and shipped an animated Plotly dashboard — cutting insight delivery from hours of manual work to under 5 minutes.
Team Project, 4 members (statistical analysis & reporting role) — DCU CSC1181 Contributed statistical analysis, the ethical/legal write-up, and final report compilation on a 70,000-patient dataset. The team's XGBoost model reached 72.93% accuracy with 5-fold stratified cross-validation; I translated those results into stakeholder-ready findings.
Solo — Anurag University Built a full solo pipeline in R — cleaning, EDA, feature selection, Random Forest training, cross-validation — and deployed it as a live tcltk GUI where a user enters wine attributes and gets an instant quality prediction. Not just a notebook; a working product.
MSc Data Analytics — Dublin City University, Ireland (Sep 2025 – Sep 2026) B.Tech Computer Science & Engineering (Data Science) — Anurag University, India — First Class with Distinction, CGPA 8.30
- BCG X Data Science Job Simulation — Forage
- Deloitte Data Analytics Job Simulation — Forage
- Database and SQL — Infosys
- Data Visualisation with Tableau — Infosys
- Big Data and Hadoop — Infosys
- Deep Learning — Scaler
- Microsoft Excel — LinkedIn Learning
I'm actively looking for Data Analyst / Junior Data Scientist roles in Ireland (hybrid or on-site, Dublin). If you're hiring or just want to talk data, reach out:
📧 durgaprasadnarsing1728@gmail.com | 🔗 LinkedIn
Data speaks — I make it understandable and useful.