Sharon M.

Sharon Muiruri

I'm a Data Scientist

About

Data Scientist & ML Engineer

I’m a data-driven and impact-oriented professional passionate about using machine learning and AI to address global challenges, especially in climate change and sustainability. With a strong foundation in machine learning and statistical analysis. I build end-to-end solutions that transform raw data into actionable insights. My goal is to drive both environmental and business value through scalable, ethical, and innovative technology.

From ETL to model deployment, I specialize in turning messy data into production-ready ML products. I leverage tools like Python, SQL, Docker, and CI/CD to ensure reliability and performance in real-world applications. Whether it's crafting data stories for field technicians or delivering dashboards for investors, I translate complex data into meaningful outcomes, and I’m always eager to keep learning and growing in the process.

Skills

Programming Languages: Python, SQL

Data Analysis & Visualization: Tableau, Power BI

Machine Learning & Deep Learning: TensorFlow, PyTorch; expertise in Regression, Classification, Clustering, NLP, Neural Networks, LLMs

Cloud Platforms: Google Cloud Platform, Azure

MLOps and Monitoring: Docker, Kubernetes

CI/CD and Automation Tools: GitHub Actions, Jenkins, Terraform

Version Control: Git

Resume

Education

Data Science & Machine Learning

2022 - 2023

Massachusetts Institute of Technology

Coursework in Python, Statistics, Machine learning, Deep learning, Computer vision and Recommendation Systems.

Bachelor of Business Information Technology

2018 - 2022

Jomo Kenyatta Universsity of Agriculture and Technology

Coursework in Object Oriented Programming, Data Structures and A lgorithms, Databases, Computer Security and Networking.

Professional Experience

Junior Machine Learning Engineer

Oct 2024 - Present

Omdena

Developed an AI-powered Crop Disease Detection model.
Built data pipelines to collect and clean 50,000+ crop images using Python and OpenCV
Trained CNN models using Tensorflow for disease classification achieving an 89% accuracy.

Machine Learning Operations Intern

Sep 2022 - Dec 2022

Flapmax AI Institute

Developed and deployed machine learning applications using FastAPI, Docker, and Kubernetes, contributing to end-to-end MLOps workflows in production environments
Built a Car Damage Detection model using Mask-RCNN.
Deployed a Commerce Marketplace SaaS Accelerator on Microsoft Azure.