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Armish B. Status: Offline
Islamabad, Pakistan
48% Job Success

Machine Learning Expert | Finance, Healthcare, Legal Prediction Models

𝐃𝐨𝐜𝐭𝐨𝐫𝐬, 𝐜𝐥𝐢𝐧𝐢𝐜𝐬, 𝐡𝐨𝐬𝐩𝐢𝐭𝐚𝐥𝐬, 𝐚𝐧𝐝 𝐡𝐞𝐚𝐥𝐭𝐡-𝐭𝐞𝐜𝐡 𝐬𝐭𝐚𝐫𝐭𝐮𝐩𝐬 — 𝐰𝐡𝐚𝐭 𝐢𝐟 𝐲𝐨𝐮 𝐜𝐨𝐮𝐥𝐝 𝐮𝐬𝐞 𝐩𝐮𝐫𝐞 𝐌𝐚𝐜𝐡𝐢𝐧𝐞 𝐋𝐞𝐚𝐫𝐧𝐢𝐧𝐠 𝐭𝐨 𝐩𝐫𝐞𝐝𝐢𝐜𝐭 𝐫𝐢𝐬𝐤, 𝐟𝐢𝐧𝐝 𝐢𝐧𝐬𝐢𝐠𝐡𝐭𝐬, 𝐚𝐧𝐝 𝐚𝐮𝐭𝐨𝐦𝐚𝐭𝐞 𝐝𝐞𝐜𝐢𝐬𝐢𝐨𝐧𝐬 — 𝐰𝐢𝐭𝐡𝐨𝐮𝐭 𝐧𝐞𝐞𝐝𝐢𝐧𝐠 𝐚 𝐝𝐞𝐞𝐩 𝐀𝐈 𝐥𝐚𝐛 𝐨𝐫 𝐛𝐢𝐠 𝐛𝐮𝐝𝐠𝐞𝐭? I’m a Healthcare Machine Learning Engineer who partners with medical professionals, clinics, and healthtech teams to turn raw clinical data into real, measurable impact. Whether you're looking to forecast patient risk, optimize hospital operations, or explore insights from years of EHR data — I deliver clean, fast, explainable ML systems that work inside real clinical environments, not just notebooks. 📊 𝐏𝐫𝐞𝐝𝐢𝐜𝐭 𝐏𝐚𝐭𝐢𝐞𝐧𝐭 𝐑𝐢𝐬𝐤, 𝐅𝐚𝐬𝐭 I craft predictive models that unlock insight from structured clinical data — think vitals, EHRs, lab results, and patient questionnaires. Using algorithms like Logistic Regression, Decision Trees, Random Forests, SVMs, and k-NN, I help healthcare teams predict disease risk, detect red flags early, and personalize care. From forecasting readmissions to scoring cardiovascular risk, my models are always tailored for interpretability, not just accuracy — because if a doctor can’t trust the model, it doesn’t belong in medicine. 🧹 𝐂𝐥𝐞𝐚𝐧 𝐘𝐨𝐮𝐫 𝐃𝐚𝐭𝐚, 𝐑𝐞𝐯𝐞𝐚𝐥 𝐈𝐧𝐬𝐢𝐠𝐡𝐭𝐬 Before any modeling begins, I take care of what most people skip — turning messy medical data into structured gold. I clean, preprocess, and engineer features using tools like Pandas, NumPy, and Scikit-learn. I deal with missing values, normalize your columns, and prepare your data pipeline so your model trains on real signals — not statistical noise. If you're not ready for ML yet, no problem. I’ll start with analysis that uncovers patterns, outliers, and trends — and guide you on what’s next. 🔍 𝐆𝐞𝐭 𝐂𝐥𝐞𝐚𝐫, 𝐄𝐱𝐩𝐥𝐚𝐢𝐧𝐚𝐛𝐥𝐞 𝐌𝐋 In medicine, a “black box” isn’t just unhelpful — it’s dangerous. I specialize in building explainable ML systems. I use SHAP, feature importance plots, confusion matrices, ROC curves, and performance dashboards to show what your model is doing, why it’s making decisions, and how to communicate those findings with clinical teams. Whether you’re reporting to investors, clinicians, or regulatory boards — I make your ML output crystal-clear and compliant. ⚙️ 𝐁𝐮𝐢𝐥𝐝 𝐈𝐭, 𝐓𝐮𝐧𝐞 𝐈𝐭, 𝐃𝐞𝐩𝐥𝐨𝐲 𝐈𝐭 I manage the full ML lifecycle — from ingesting raw datasets to delivering deployed endpoints and ready-to-use models. I build pipelines using Scikit-learn and PyCaret, fine-tune hyperparameters with GridSearchCV, validate with cross-validation techniques, and deploy models using FastAPI for real-time prediction or internal testing. Need to track experiments or scale across versions? I’ve got you covered with MLflow integration and clean model versioning. My goal: make ML usable, repeatable, and rock solid in your workflow. 💙 𝐖𝐡𝐲 𝐂𝐥𝐢𝐞𝐧𝐭𝐬 𝐓𝐫𝐮𝐬𝐭 𝐌𝐞 I don’t build models for research papers — I build them for the real-world. Clients appreciate that I combine solid machine learning knowledge with a practical understanding of clinical workflows. My communication is clear and jargon-free, my deliverables are clean and well-documented, and I stay focused on outcomes that actually matter: accuracy, trust, and actionability. You’ll always know what I’m doing, why I’m doing it, and how it will help your patients or product succeed.
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