About
AI/ML undergraduate specializing in healthcare data analytics, with hands-on experience building two end-to-end healthcare data platforms: a FHIR-based hospital analytics warehouse and a CMS Hospital Price Transparency pricing-intelligence pipeline. Comfortable owning a dataset across its full lifecycle — ingesting messy, real-world healthcare data (FHIR clinical resources, hospital pricing MRFs), normalizing it into validated relational schemas, and delivering SQL analytics and Power BI dashboards that support payer/provider benchmarking, utilization analysis, and reporting. Strong foundation in Python, SQL, data quality engineering, and machine learning.
Skills & Expertise (35)
Work Experience
Developer
CareSight
Present - Present
Built an end-to-end pipeline (FHIR → Python ETL → PostgreSQL data warehouse → SQL analytics → Power BI) that transforms raw FHIR healthcare resources into analysis-ready datasets spanning 10 patients, 382 encounters, 269 conditions, 1,751 observations, 1,086 procedures, and 119 medication requests. Designed a dimensional healthcare data warehouse in PostgreSQL (dim_patient plus fact tables for encounters, conditions, observations, procedures, and medications) with primary/foreign-key referential integrity. Authored reusable Python ETL transformers per FHIR resource type using Pandas and SQLAlchemy, maintaining consistency across patients, encounters, and clinical events. Wrote a library of SQL analytical views (patient-360, encounter, condition, observation, procedure, and medication analytics) and dedicated KPI views to power a 3-page interactive Power BI dashboard (Executive Overview, Patients & Demographics, Clinical Analysis). Implemented multi-stage data validation — CSV schema checks, PostgreSQL constraint checks, and referential-integrity testing — confirming zero orphan records across every fact-to-dimension relationship.
Developer
Hospital Price Intelligence (HPI)
Present - Present
Built a healthcare analytics platform that ingests, normalizes, and validates CMS Hospital Price Transparency Machine-Readable Files (MRFs), converting complex, semi-structured hospital pricing JSON into standardized relational schemas. Engineered a custom JSON parser and database-build pipeline in Python to reconcile inconsistent, hospital-specific pricing file structures into one unified schema. Modeled analytical DuckDB marts enabling fast, serverless SQL analysis of negotiated hospital rates without a database server. Built a dedicated data-quality module backed by an automated pytest test suite to validate ingestion output before it reaches the analytics layer. Enabled SQL-driven analysis of payer parity, contract variation, and price dispersion across healthcare services — the same class of analysis used in price-transparency and reimbursement benchmarking work.
Education
B.Tech, Computer Science & Engineering (AI/ML) - Matoshri Pratishthan Group of Institutions, School of Engineering
2022 - 2026 · Afghanistan
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