Hi, I'm
Hamid
A Data Analyst based in the United States. I'm passionate about using data to solve real-world problems.
I'm currently pursuing an MS in Business Intelligence and Analytics at Stevens Institute of Technology.
Feel free to check out my resume—I'd be happy to connect and collaborate!
About Me
I love transforming complex data into actionable insights—I’ve tackled projects like centralizing raw records into a supply chain data warehouse, optimizing mobile gaming metrics, and building predictive models within the healthcare industry.
When I’m not debugging code or crunching numbers, you can find me lost in a new book—transitioning from a Sally Rooney phase to exploring Claire Keegan’s understated brilliance—or daydreaming about my next excursion into classical Western literature, museums, operas, new dining spots, or scenic trails.
- Languages: SQL, Python, MongoDB
- Tools: Microsoft Power BI, Tableau, Alteryx, MySQL Workbench, Microsoft Office Suite (Excel, Word, PowerPoint), LaTeX
- Certifications: Data Analytics Specialization (Google)
Work Experience
Research Assistant - Viral Diseases, Medications, and Reinforcement Learning
May 2024 – August 2024 | Hoboken, NJ
- Designing optimal drug administration policies under the supervision of Dr. Choudur Lakshminarayan, focusing on improving treatment strategies for women with HIV using different clinical designs.
- Applying statistical modeling and machine learning techniques—including Logistic Regression and Reinforcement Learning (e.g., Q-Learning, Markov Chains, MDP)—to model treatment efficacy.
- Analyzing virus behavior, drug actions, and biomarker rewards by defining state-space (S), action sets (A), rewards (R), transition probabilities, and discount factors (γ) to optimize strategies.
- Generating Q-Tables with Q-values to identify the most effective drug actions, optimizing policies by selecting actions with the highest expected rewards.
- Drafting technical documentation in LaTeX for a Design of Experiments paper, incorporating Multivariate Analysis concepts such as Least Significant Differences.
Projects
E-Commerce & Supply Chain Data Warehouse
Developing a PostgreSQL staging schema to centralize 100k+ raw e-commerce records (orders, customers, products) and automated SQL ingestion scripts for reproducible table creation with robust quality checks, enhancing data reliability for dimensional modeling and advanced BI reporting
Patient Opportunity Model
Leveraged synthetic generated data to build a Patient Opportunity Model for lung cancer treatments. This repository includes Jupyter notebooks for predicting therapy initiation and switching, analyzing Lines of Therapy (LOT), and extracting key insights for pharmaceutical Sales & Marketing
Machine Learning for HIV Drug Optimization
Using machine learning techniques (Q-Learning & Logistic Regression) to come up with optimal drug policies for women with HIV
Anesthesia Market Cannibalization Analysis
Analysis of injectable anesthesia market dynamics and strategy to address cannibalization. Includes data prep, claims analysis, and actionable insights
Breast Cancer Logistic Regression
Classification of breast cancer tumors (Benign or Malignant) using Logistic Regression with L1 and L2 regularization on the Breast Cancer Wisconsin dataset
CVM Medicare Insights
This repository contains a comprehensive data analysis of Medicare Part A & Part B claims focusing on CVM conditions. Leverages data cleaning, quality checks, segmentation, and visualization techniques to extract meaningful insights into healthcare provider prescribing behaviors
Walmart SQL Database Schema
Walmart (hypothetical) database with data, along with an ERD diagram and sample queries
Titanic Survival Decision Trees
Optimized Decision Tree and Ensemble Learning models for predicting Titanic passenger survival, with hyperparameter tuning and Random Forest comparison