A final-year student with a biotech mind and an analyst's toolkit — I turn messy, real-world data into decisions people can act on. Ten shipped projects, from warehouses and risk models to a fraud-detection audit engine.
I'm a Biotechnology student at Amity University, Noida who believes the best way to learn something is to start before you feel ready.
That's how I ended up interning at IIT, competing at national hackathons, and spending two years in a research lab. Data analysis is where that instinct meets a real skill — I'm drawn to the moment when numbers stop being numbers and start telling you something true about a patient, a business, or a decision that needs to be made. I'm working towards roles in finance, healthcare, and consulting analytics.
Vienna waits for you — so there's time to build something worth arriving at.
Every project below is a real dataset, a real question, and a result someone could act on. Full code, data, and write-ups on GitHub.
An end-to-end analytics warehouse over 100K+ rows of AMFI-style mutual-fund data — a MySQL star schema, a tested Python ETL pipeline, automated data-quality gates, and an Excel dashboard that turns ten raw CSV feeds into board-ready industry metrics.
Predicts credit-card default on 30,000 real clients and turns the model into a money decision — imbalanced classification judged on precision-recall, a cost-based approve/decline threshold, and SHAP explainability that a credit officer (and a regulator) can actually act on. The core analytics job at a card issuer.
Predicts 30-day hospital readmission on 101,766 real patient encounters — SQL cohort analysis, hypothesis testing, and a risk model that ranks patients before discharge so care teams can intervene where it actually matters.
Ask "which fund has the lowest expense ratio?" and get a cited answer. A retrieval-augmented Q&A engine over 40 factsheets generated from the warehouse above — a zero-cost structured answer engine, with optional Claude synthesis for open-ended questions.
Ranks 200+ NY hospitals by billing-outlier risk across 111,155 real claims lines and screens the provider network against the 83,464-entry federal exclusion list — the payment-integrity workflow at Optum, a Blue plan, or CMS. Two independent detectors (peer-benchmark markup + Isolation Forest) have to agree before a facility hits the priority audit queue, cutting false positives.
Analysed 64,764 CMS records across 4,239 hospitals to find which conditions, states, and hospitals drive 30-day readmission risk — and whether size or prestige actually predicts performance.
Analysed 507,521 real SEC settlement-failure records to locate where operational risk concentrates, when stress events hit, and how to tell chronic failures from event-driven spikes.
Forecast 10-year US healthcare spending across 6 CMS service lines — benchmarking Prophet, ARIMA, and Holt-Winters on a 5-year holdout to find which model wins where, and why.
Classifies fungal disease risk across 9 pathogen types from ecological trait data — applicable to pharma R&D, agricultural risk, and life-sciences analytics.
An end-to-end Flask app that predicts academic outcomes and generates a Student Success Index with personalised recommendations — the same pattern as patient risk scoring and churn.
Finance, healthcare, or consulting — if you're working on something data-driven and want someone who pairs domain curiosity with analytical rigour, let's talk.