Data Analyst – Healthcare & AI

Hi, I'm Aswin Anil Bindu.

I'm a data analyst with 2+ years of experience transforming complex datasets into clear, actionable insights. I specialize in Python, SQL, Tableau, and Power BI, building predictive models, dashboards, and data stories that improve decision-making in healthcare, finance, and public-sector environments.

View Projects Download Resume
Location Toronto, Canada
Focus Areas Healthcare analytics, AI, accessibility

About

I'm a data analyst with hands-on experience in statistical modeling, predictive analytics, and BI reporting. I've built machine learning models for retail banking, developed dashboards that improved operational visibility, and delivered insights that enhanced efficiency and cost optimization.

My background blends engineering, data science, and real-world analytics using Python, SQL, Tableau, and Power BI. Now based in Toronto, I'm pursuing the Applied A.I. Solutions Development program at George Brown College, focusing on practical AI applications and healthcare analytics.

I'm passionate about applying data and AI to healthcare and public-sector challenges — improving accessibility, patient outcomes, and evidence-based decision-making. I'm actively building a portfolio centered on predictive modeling, healthcare dashboards, and applied AI.

Current Focus

  • Building healthcare-focused ML and analytics projects
  • Advancing Python and SQL for data engineering tasks
  • Designing clean, production-ready dashboards in Tableau & Power BI
  • Strengthening communication and interview readiness

Projects

Ontario ED Intelligence Platform (AI + Health Operations + Cloud)

Python · XGBoost · Prophet · FastAPI · Streamlit · Docker · Azure

AI-powered emergency department analytics platform for Ontario hospitals: surge forecasting, health equity mapping, ALC bed block risk scoring, and prescription anomaly detection.

  • Built 4-module healthcare analytics suite using Prophet, XGBoost + SHAP, and Isolation Forest.
  • Key outcomes: ALC ROC-AUC 0.984, Rx anomaly precision/recall 0.812/0.812, and 137 predicted surge days across 6 hospitals.
  • Production deployment on Azure Container Apps with FastAPI API + Streamlit dashboard via Docker and GitHub Actions CI.
GitHub Repository Live Dashboard API Docs

Brain MRI Tumor Detector (Deep Learning + Cloud Deployment)

Python · PyTorch · FastAPI · Docker · Azure

Production-deployed clinical web application that classifies brain MRI scans as Tumor or No Tumor using an ensemble deep learning pipeline.

  • Trained and benchmarked ResNet18, VGG16, DenseNet121, EfficientNetB0, and MobileNetV2.
  • Ensemble prediction improved performance by ~2–5% over single-model inference.
  • Containerized with Docker and deployed to Azure App Service via Azure Container Registry.
GitHub Repository Live App

Ontario ER Wait Time Analysis (EDA + Dashboard)

Python · Public Health Data · Tableau

Exploratory analysis of Ontario emergency department wait-time data to uncover hospital-level trends, regional gaps, and seasonal patterns for healthcare decision support.

  • Cleaned and merged raw CSV datasets from Ontario public health sources.
  • Analyzed 90th-percentile wait times by hospital, region, and time period.
  • Built Tableau dashboard with KPI and trend views for planners and stakeholders.
GitHub Repository Tableau Dashboard

Healthcare: Diabetes Prediction (ML Classification)

Python · scikit-learn · EDA · Predictive Modeling

End-to-end ML pipeline to predict diabetes risk from clinical features, with emphasis on model comparison, reproducibility, and reducing false negatives for high-risk patients.

  • Compared Logistic Regression, KNN, and Random Forest performance.
  • Prioritized recall and evaluated with robust classification metrics.
  • Documented full workflow in reproducible Jupyter notebooks.
GitHub Repository

Thief Detection System (AI Computer Vision)

Python · OpenCV · Computer Vision · Real-Time Detection

Real-time security monitoring system that detects intruders from webcam feed and triggers recording with visual alerts and timestamps.

  • Implemented frame differencing pipeline: grayscale → blur → threshold → dilate → contours.
  • Displays SAFE/UNSAFE status overlays with bounding boxes.
  • Auto-saves MP4 evidence and logs intruder detections in real time.
GitHub Repository

Skills

Technical

  • Python (pandas, NumPy, scikit-learn)
  • SQL (MySQL, SQL Server)
  • Jupyter Notebook, Streamlit

Tools

  • Git & GitHub
  • VS Code, Jupyter
  • Linux Basics & PowerShell

Analytics & BI

  • Power BI, Tableau Public
  • EDA & Data Visualization
  • Dashboard Design

Soft Skills

  • Problem-solving under constraints
  • Clear documentation
  • Collaborative teamwork

Machine Learning

  • Classification & Regression
  • Clustering & Basic NLP
  • Feature Engineering & Evaluation

Data Management

  • SQL Databases, MongoDB
  • ETL Workflows
  • Data Modeling

Education

Applied AI Solutions Development (Postgraduate Certificate)

George Brown College · 2025 – 2026

Practical training in machine learning, predictive modeling, NLP, and AI solution development. Focused on healthcare analytics and applied portfolio projects.

Bachelor of Engineering – Mechanical Engineering

Anna University · 2015 – 2019

Built strong analytical, quantitative, and problem-solving foundations through engineering coursework and collaborative technical projects.

Experience

AI Assistant Team Lead (Applied AI Project) – Kinectrics

Mar 2026 – Present · Internship · Toronto, Ontario, Canada (Remote)

  • Lead a cross-functional team to design and develop an AI assistant that improves enterprise knowledge retrieval workflows.
  • Define project scope, data requirements, and technical architecture, including NLP pipelines and knowledge-base integration.
  • Coordinate model experimentation and deployment planning to ensure production readiness and stakeholder alignment.

Machine Learning Intern – Citi

Jan 2023 – Jan 2024 · Remote

  • Developed and fine-tuned ML models using scikit-learn and TensorFlow for customer segmentation and campaign optimization.
  • Analyzed large-scale banking datasets to detect anomalies and support fraud-detection workflows.
  • Built data pipelines that improved decision-making across retail banking teams.
  • Improved targeted marketing effectiveness by 15% through predictive modeling.

Junior Data Analyst – Luminar Technolab

Jul 2021 – Jul 2023 · India

  • Cleaned, transformed, and analyzed large datasets using Python and SQL to support business planning and reporting.
  • Developed Tableau and Power BI dashboards that improved operational visibility and faster stakeholder decisions.
  • Applied statistical analysis to identify cost-saving opportunities and improve team efficiency by 10%.
  • Implemented data-validation workflows that improved reporting accuracy and reduced manual rework.

Data Science Intern – Luminar Technolab

Jul 2020 – Jun 2021 · India

  • Built predictive models that improved targeted marketing performance by 15%.
  • Cleaned, processed, and analyzed datasets using Python, pandas, NumPy, and SQL.
  • Created Tableau dashboards that helped stakeholders interpret trends and patterns more effectively.
  • Collaborated with cross-functional teams to translate business requirements into scalable data solutions.

Contact

I'm open to opportunities in healthcare analytics, AI-assisted data workflows, and public-sector data roles. If my work aligns with what your team is building, I'd be happy to connect.

Email aswinanilbindu@gmail.com
GitHub github.com/Aswinab97
LinkedIn linkedin.com/in/aswinab