Turning Raw Data Into
Intelligence.

BS & MS in Computer Science (WGU) · AWS Certified Machine Learning Engineer (MLA-C01) · ITILv4 · Linux Hands-on experience analyzing City of Buffalo open datasets and building scalable data pipelines.

Python SQL ETL Pipelines AWS ML (MLA-C01) Cloud & MLOps Linux
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Mission-Oriented Analytics

I am a data professional with a B.S. in Computer Science from WGU, currently pursuing an M.S. in Computer Science (AI/ML). I specialize in transforming messy, multi-source datasets into actionable intelligence using ETL pipelines, statistical analysis, and cloud-ready architectures.

Education & Certifications

AWS Certified Machine Learning Engineer – Associate

AWS

Building, training, and deploying ML models on AWS. Experience with SageMaker, pipelines, and MLOps workflows.

B.S. Computer Science

Western Governors University

M.S. Computer Science (In Progress)

Western Governors University

ITIL v4 Foundation

LPI Linux Essentials

Technical Skills

Languages & Databases

  • Python
  • SQL (PostgreSQL/MySQL)
  • Bash

Data Engineering

  • ETL Pipelines (Local & Cloud)
  • Pandas / NumPy
  • Data Quality Validation

Machine Learning

  • Scikit-learn / NLP / Model Deployment
  • Data Visualization

Cloud & DevOps

  • AWS (S3, EC2, Lambda, SageMaker)
  • CI/CD Concepts
  • Linux Systems

Projects

Buffalo Landlord Analysis

Investigated housing violations using multiple city datasets. Built ETL pipelines and designed analysis scalable for cloud deployment.

  • 2.57x higher violations for non-local landlords
  • Identified major resolution gaps
  • AWS-ready architecture for scaling pipelines

Buffalo 311 Analysis

Analyzed service request disparities across neighborhoods and uncovered inefficiencies in response times.

Contact

Email: mhoss43@proton.me

GitHub: github.com/mdintisarhossain

Location: Buffalo, NY