Alec Morgan

Alec Morgan
360-860-2516
AlecNMorgan@gmail.com
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Data scientist with applied experience in data analysis and ML utilizing scikit-learn and Keras. In my previous work I exceeded expectations by innovating and improving upon existing processes in addition to seeing them carried out. I have a proven history of helping drive projects to success through teamwork, building robust reusable code, and leveraging my diverse skill set in machine learning and data analytics.

TECHNICAL SKILLS

Python, scikit-learn, SQL, Pandas, Seaborn, Matplotlib, Keras, TensorFlow 2.0, Git, NumPy, DRY, OOP, web scraping, Json

TECHNICAL PROJECTS

Image Tagger – Github
An ensemble model that automatically adds hashtags to images
+ Utilized Selenium to scrape thousands of images and hashtags from Instagram
+ Deployed pretrained neural network using Keras to solve cold start problem
+ Integrated with team’s ALS hashtag generator to create an all-in-one solution

Deep Learning Library – Github
A library of industry-standard deep learning algorithms
+ Built DRY codebase to enable better code reusability and extensibility
+ Utilized NumPy to improve performance, readability, and maintainability
+ Created multiple architecture demos to showcase library capabilities

Housing Price Predictor – Github
A housing price prediction model built using machine learning
+ Employed scikit-learn linear regression model to generate price predictions
+ Optimized model using scikit-learn model validation suite to improve accuracy
+ Rendered data using Matplotlib to present and share insights

Music Industry Hypothesis Evaluation – Github
A scientific analysis of the optimal brands for musicians to build
+ Used PostgreSQL database to make music review data persistent and accessible
+ Analyzed data using statsmodels and scikit-learn to verify statistical significance
+ Visualized insights using Matplotlib and Seaborn to make complex data intuitive

EMPLOYMENT HISTORY

XPO Logistics Supply Chain, Everett, WA
Inventory Specialist, 11/2017 – 12/2018
+ Ensured inventory accuracy for an average of 100,000 parts daily
+ Created new VIB (Visual Identification Badge) design with better readability on own initiative
+ Improved VIB creation process by streamlining, updating, and thoroughly documenting steps
+ Updated hundreds of VIBs with better image quality and design
+ Promoted from Material Handler to Inventory Specialist within several months of hire

EDUCATION

Flatiron School – 2019
+ Immersive Data Science Program
GED – 2017
+ General Education Diploma with college-ready scores