Machine Learning Data Scientist

Experienced Data Scientist and Machine Learning Engineer with over a decade of successful experience . Skilled in engineering machine learning models, optimizing algorithms, and mentoring others. Recognized for revolutionizing processes, slashing processing times, and fostering collaborative environments. Proficient in Python, SQL, and data visualization tools. Committed to continuous learning and innovation in the field.

Skill

Experience

Gabriel Thomas

Data Scientist and Machine Learning Engineer

*******.*.**********@*****.*** +1-803-***-****

10682 two notch road, Elgin, South Carolina, 29045 Programming Languages

Deep Learning Frameworks

Machine Learning and Data Science

Text Processing and NLP

Data Visualization

APIs and Backend FastAPI Database

Development and Deployment

Systems

Senior Data Scientist and Machine Learning Engineer Developed machine learning models to predict vehicle travel times, reducing end-of-route time-of-arrival errors by 30%. Validated models using Google API and GPS data. Implemented and evaluated various machine learning algorithms such as Support Vector Machines, Random Forests/XGBoost, and Neural Networks. Identified XGBoost/RandomForest as the most effective models. Optimized 3D object extraction and clustering algorithms, significantly reducing processing time from 20 minutes to 0.5 seconds and clustering time from 2 hours to 3 seconds by leveraging graph algorithms and dynamic programming.

Enhanced efficiency of service docker containers through multi-stage build processes, decreasing build time from 20 minutes to 70 seconds and lowering storage requirements by 30%. Designed a robust and scalable routing engine wrapper API using FastAPI. Managed a comprehensive ETL process involving multiple data sources, utilizing the Polars library for a performance enhancement of over 1000x.

Created an Entity-Relationship Diagram (ERD) comprising 10 tables with 5-20 columns each, implementing it in a PostgreSQL database.

Sep 2022 - May 2024

Senior Python Developer

Built a high-performance streamline simulation software from the ground up. Developed a Python-based interface for the software, integrating a user-friendly graphical user interface

(GUI) with PyQT, and enabling real-time 3D visualizations using VTK/PyVTK. Implemented advanced data manipulation algorithms to preprocess and post-process simulation data, improving data quality and analysis efficiency.

Designed and implemented optimization algorithms to enhance the simulation engine's performance, resulting in a significant improvement of approximately 20%. Jan 2018 - Aug 2022

Fingent New York, NY

Innowise New York,NY

: Python, SQL, C++, Matlab, Bash

: PyTorch, Tensorflow

: Scikit-Learn, Numpy, Pandas, Statistics

: SpaCy

: Matplotlib, Plotly

: PostgreSQL, MongoDB

: Azure, Docker, Git

: Windows, Linux

linkedin.com/in/gabriel-thomas-803067161

Soft Skills

Bachelor's degree in Computer Science

University of South Carolina Sep 2012- Jun 2016

Education

Self-Motivation: Excel in tackling open-ended problems and achieving broadly-defined goals. Problem-Solving: Possess strong analytical and critical thinking skills. Attention to Detail: Highly focused on verifying data quality. Teamwork: Experienced in collaborative environments. Communication: Able to convey complex technical ideas in simple terms. Machine Learning Specialization Stanford University (Coursera) Practical Deep Learning For Coders by Jeremy Howard Fast.ai PostgreSQL for Everybody Specialization University of Michigan (Coursera) MongoDB Python Developer Path MongoDB University

Modern APIs with FastAPI and Python Course TalkPython Docker and Kubernetes: The Complete Guide Udemy

The Complete Python Bootcamp From Zero to Hero in Python Udemy Courses

Experience

Deep Learning Engineer

Developed statistical models using Bayesian inference and advanced machine learning methods to analyze trading data and forecast market trends, improving decision-making and trading strategies. Utilized TensorFlow, Scikit-learn, and Keras to construct neural network models grounded in deep learning and data mining technologies, enhancing predictive capabilities. Presented findings and recommendations to senior executives, outlining strategies for profitability enhancement and risk mitigation through machine learning and artificial intelligence techniques, facilitating informed decision-making.

Aug 2016 - Jan 2018

Datadog New York, NY

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