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michael-gurule/README.md

Hi, I'm Michael Gurule

Data Scientist | Former Strategy Consultant | Production ML Engineer

Transitioning from 8 years of Fortune 500 consulting to data science roles, with a focus on production-grade ML systems and business-driven analytics.


About Me

  • Currently building production ML systems and advanced analytics projects
  • MS Data Science + AWS Certified Data Engineer + Google Advanced Data Analytics
  • Former Senior Strategy Consultant at Sedgwick and JS Held
  • Based in Colorado
  • Seeking Senior Data Scientist / ML Engineer roles

What sets me apart: I combine deep technical ML skills with 8 years of Fortune 500 client experience. I don't just build models—I build production systems that deliver measurable business impact.


Currently under active development

A production-grade machine learning platform demonstrating advanced sensor fusion techniques for Defense applications. Integrates Overhead Persistent Infrared (OPIR) thermal detection with Radio Frequency (RF) geolocation algorithms for real-time threat detection and tracking.

Deployed Features

Multi-Sensor Fusion Engine

  • Implements Kalman filtering with covariance-weighted measurement fusion
  • Mahalanobis distance data association for multi-target tracking
  • Real-time track quality assessment and uncertainty quantification

RF Geolocation Algorithms

  • TDOA/FDOA positioning using nonlinear least-squares optimization
  • Hybrid time-frequency solver for improved accuracy
  • GDOP/PDOP computation for sensor geometry assessment
  • Mixed-altitude sensor network design (500m-2000m) for optimal 3D positioning

Deep Learning Pipeline

  • 1D CNN for thermal event classification (5 classes)
  • PyTorch training pipeline with early stopping and learning rate scheduling
  • 10,000+ physics-based synthetic training samples

Features Under Development

  • Interactive Streamlit dashboard for real-time track visualization
  • 3D sensor network and track position plotting
  • Multi-Hypothesis Tracking (MHT) for improved ambiguity resolution
  • Extended Kalman Filter (EKF) for nonlinear motion models
  • Additional Sensor Modalities EO/IR (Electro-Optical/Infrared) SAR (Synthetic Aperture Radar)

Portfolio Projects

Real-time multi-hazard risk assessment integrating USGS, NASA, and NOAA data sources.

  • Tech Stack: Python, FastAPI, Streamlit, Pandas, Plotly
  • Highlights: Multi-source API integration, geographic risk scoring, production error handling
  • Business Value: Portfolio risk assessment for real estate and insurance industries

Production ML pipeline with cost-optimized decision thresholds delivering $474K monthly savings.

  • Tech Stack: Python, XGBoost, FastAPI, Streamlit
  • Highlights: Custom cost functions, sub-100ms API latency, interactive monitoring
  • Business Value: Optimized precision-recall tradeoff based on real business costs

Advanced causal methods (PSM, DiD, Uplift) to measure true incremental marketing impact.

  • Tech Stack: Python, scikit-learn, statsmodels, DoWhy, CausalML
  • Highlights: Propensity score matching, difference-in-differences, CATE estimation
  • Business Value: Separates correlation from causation in marketing ROI analysis

Technical Skills

Languages & Core:
Python SQL R

ML & Data Science:
scikit-learn XGBoost Pandas NumPy

Production & APIs:
FastAPI Streamlit Docker

Cloud & Data:
AWS PostgreSQL

Specializations:

  • Production ML Systems & MLOps
  • Causal Inference & Experimental Design
  • Business Analytics & Strategy
  • API Development & Data Engineering

Certifications

  • MS Data Science - In Progress
  • AWS Certified Data Engineer – Associate
  • Google Advanced Data Analytics Professional Certificate

Let's Connect

LinkedIn Email Medium

Open to opportunities in data science, ML engineering, and analytics roles. Particularly interested in companies solving real-world problems with data.


From michael-gurule

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  1. fraud-detection-system fraud-detection-system Public

    A production-ready machine learning system for detecting credit card fraud in real-time with sub-100ms latency. Built with XGBoost, FastAPI, and Streamlit.

    Python 1

  2. marketing-attribution-causal-inference marketing-attribution-causal-inference Public

    Causal inference system for marketing attribution using PSM, DiD, and uplift modeling with interactive Streamlit dashboard

    Python 1

  3. disaster-risk-platform disaster-risk-platform Public

    A production-grade data pipeline that ingests real-time data from government APIs (USGS, NASA, NOAA) to assess natural disaster risk across earthquakes, wildfires, and severe weather.

    Python 1

  4. sentinel-multi-intel-platform sentinel-multi-intel-platform Public

    Python 1