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Click here or scroll down to respond to this candidateCandidate's Name
PHONE NUMBER AVAILABLEDix Hills New York EMAIL AVAILABLE LINKEDIN LINK AVAILABLE Operating System Developer and Data Science Professional Experienced in building innovative solutions across Data Science, Machine Learning, and Software Development. Key projects include: Built an LSTM Deep Learning Tesla stock trading Machine Learning application. Developed a JavaScript application for stock trading profit management. Created Tesla, Bitcoin, and Dogecoin Machine Learning trading prediction applications using linear regression algorithm and the Python programming language. Developed a Bitcoin investing prediction application using R and linear regression. Built an S&P 500 Machine Learning model in Python to predict stock movements using linear regression algorithm. Built an Image Recognition Artificial Intelligence software application to predict malaria infection in red blood cell images.In addition to these projects, I have developed a custom x86_64-bit operating system, successfully booted on QEMU emulator and deployed via USB disk on a custom-built machine. I am currently pursuing a Master's in Data Science and Analytics degree at Eastern University, St. Davids, PA. Holder of two graduate-level certificates in Data Science and Machine Learning from MIT, specifically in Applied Data Science and Machine Learning. A Stony Brook University graduate and ASCP-certified Clinical Laboratory Scientist, I am also a Google Certified IT Support Professional. My recent MIT certifications provided in-depth exposure to key Machine Learning techniques, including Linear and Logistic Regression, Decision Trees, Random Forests, Deep Learning, Support Vector Machines, K-Nearest Neighbor, K-Means, Dimensionality Reduction, Gradient Descent, and Neural Networks. Additionally, I hold the Google IT Support Professional Certificate, a comprehensive program covering IT support, system administration (Linux and Windows), bash shell scripting, and Windows PowerShell. Actively competing in Data Science and Machine Learning hackathons on Kaggle, I build predictive models to tackle complex real-world challenges. I am now seeking a position as a Data Scientist, Machine Learning Engineer, or Software Developer to apply my technical expertise and drive innovative solutions. WORK & RELEVANT EXPERIENCEUsed cloud platform at https://bryerstoneapps.pythonanywhere.com/ to host many Python web applications including a presidential prediction Python web application that uses natural language processing for prediction.Used Ubuntu 20.04 and Debian 11 Linux Distros command line to develop a deployable version of Bryerstone Cloud using OpenStack Cloud technology. Built Machine Learning projects such as Recommendation Systems, Linear Regression models, Binary Classification Systems, Logistic Regression models utilizing the sigmoid functions, Deep Learning models and more.Conducted Hypothesis testing study by collecting data and found evidence to reject testing policy at an organization and used said collected data to predict subpar delivery of service based on findings discovered by the Hypothesis testing study conducted. Built a x86_64-bit Operating System that currently boots up on QEMU emulator and burnt it on USB disk drive and currently adding security features to all C-language and assembly language files. Built a LSTM Deep Learning Tesla stock trading Machine Learning application. Built a JavaScript application for stock trading profit management. Built Tesla, Bitcoin, and Dogecoin Machine Learning trading prediction applications using linear regression in python.Used the R Computer Programming Language to build a Bitcoin investing prediction application using linear regression algorithm.Built S&P 500 Machine Learning Model to Predict movement of S&P 500 stocks using linear regression algorithm.Built a dedicated server computer with GPU to further test self-built and newly-built Operating System for handling Machine Learning and Deep Learning tasks. Built two Linear Regression Machine Learning trading applications for trading stocks and cryptocurrency and made enough profits to buy a house for cash in the Poconos, 2106 Lakeview Road, Bushkill, PA. Built a XGBoost Random Forest classification Machine Learning application and use it to compete in the 2023 MIT Japanese Speed Train Hackathon and came away with a performance accuracy of 91.7% on the leaderboard.Currently participating in the Kaggle Data Science competition using Decision Trees and Random Forest classifier models to predict Age-Related conditions and Non-Age-Related conditions. Used Python Pandas library to analyze datasets and to assist in building Machine Learning (ML) Models. Used Python Numpy library to help with mathematical operations when analyzing datasets and building Machine Learning models.Self-built a Gradient Descent Python application.Self-built a Python application that calculates the R-square, Root Mean Square Error, Mean Square Error, Mean Absolute Error to evaluate the performance of a self-built Linear Regression Machine Learning model used for predicting cryptocurrency prices and stock prices. Performed Dimensionality Reduction techniques on complex models using PCA and S-Net. Built Machine Learning Projects using Linear Regression Algorithms, Logistic Regression Algorithms, Sigmoid Function-Based Algorithms.Built Machine Learning Model using SVM and Decision Trees Algorithm. Built a loss function algorithm using Mean Square Error formula to display how increasing sample size increases the accuracy of Machine Learning Linear Regression Models. Conduct data visualization using Bar Plots, Scatter Plots, Box Plots, QQ plots, Linear Regression plots, and more.Used Python Matplotlib library to visualize and analyze datasets and to assist in building machine learning models.Used Python Seaborn library to visualize and analyze datasets. Used Python Jupyter Notebook as a code editor in building Python Machine Learning Applications. Used Python Sklearn library for building Machine Learning Applications using Logistic Regression Used Python Sklearn Machine Learning algorithms, Train_test_split, GridSearchCV, MinMaxScaler, LabelEncoder, OneHotEncoder.Used Google Colabortory to build Machine Learning Applications. Use Personally-built Linux server to build Machine Learning Applications. Used Python Sklearn Decision-Tree- Classier and Random-Forest- Classifier algorithms to build Machine Learning Applications.Used Python Scipy library for implementing the entropy algorithm in Machine Learning Application Development.Used Pip and Conda to install python packages.Used Sklearn Imputer algorithm to handle missing values in data before splitting and building ML models.Used Python Anaconda to launch Jupyter Notebook for Machine Learning Application Development. Used Python Pandas DataFrame to create datasets from scratch for building Machine Learning Applications.Built Tensorflow-GPU python virtual environments with CUDA, CUDNN support for Deep Learning, Neural Network Application Development via Jupyter Notebook and Anaconda-Navigator. Built a Movie Machine Learning Recommendation system to increase sales of movies by said company using Deep Learning, Neural Networks.Build Python Machine Learning applications that reads dataset presented in excel file format. Built Machine Learning Model to reduce hotel customer reservation cancellation rates using Logistic regression algorithms.Built Machine Learning Predictive model to predict price movement of Crypto currency Dogecoin using Linear Regression Algorithm.Used Python R-Square Accuracy function to test percent accuracy of Linear Regression Machine Learning Model.Built Pima Diabetes Machine Learning Model to identify if multiple pregnancies cause diabetes in women.Built S&P 500 Machine Learning Model to Predict movement of S&P 500 stocks using linear regression. Used Statistical principles to analyze data in datasets. Currently developing a gradient descent algorithm from scratch for fun. Built Mean Absolute Error Python function using the Mean Absolute value formula to see how it works. Built Mean Square Error Python function using the Mean Square Error formula to see how it works. Built Root Mean Square Error Python function using the Root Mean Square Error formula to see how it works.Built an Entropy Python function using the Entropy formula to see how it works. Possess knowledge of laboratory computer system analysis, program techniques, computer language, and program design sufficient to implement various laboratory associated packages and sustain operation of the laboratory system.Completed C Computer Language certificate course: Introduction to C Programming Variables Input Output, a project driven-course in the C Computer Language: [Aug 8, 2022]. Familiar with the following computer programming languages, Mumps, Assembly Language, Java, Python, R, C++, C, JavaScript, React, PHP and also built software applications using Python, C, R, C++, JavaScript, React, PHP and Java.Possess knowledge of concepts, principles and methodology of clinical laboratory technology in relation to laboratory information systems.Possess knowledge and understanding of laboratory operations and their relationship to the organization sufficient to provide advisory, inspection, training and problem-solving services on specific projects, programs or functions.Possess the ability to adapt, implement, and integrate the use of software to specific laboratory applications and processes, including the use of office automation software. Installed and currently maintains a demo version of VISTA/CPRS Electronic Health Record system on Windows Server 2019 at home office for learning purposes. Possess the ability to independently plan, organize, set priorities, work as a team member and effectively complete assignments.Possess knowledge of compliance and regulatory requirements for laboratory functions. Possess advanced knowledge of the Mumps Computer Language and its relation to the VISTA/CPRS Electronic Health Record System and the Laboratory Package. Aware of the new auto verification feature added to the Laboratory Package by the Office of Information & Technology (OI&T), which fosters a reduction in turnaround time. Aware of the Veterans Administrations Electronic Health Record modernization initiative, in which the department has switched to Cerner Electronic Health Record system, and is currently implementing the new system at selected VA Medical centers. Installed and currently maintaining a demo version of VISTA/CPRS Electronic Health Record system on Windows Server 2019 at my Home Lab, (made possible by WorldVista EHR Systems): [Sept, 2022 to present].Implemented and integrated opensource software technologies such as postfix and dovecot to build a viable and professional email server for glenford@diagnosischeck.com. Used Data Analytics techniques and statistics principles with tools such as Microsoft Excel to identify trends in financial markets: [July, 2020 to present]. Developed computer algorithms that statistically analyze financial market data in CSV files to predict market movements: [July, 2020 to present].Performed patient processing on Cerner Electronic Health Record system: [Jan, 2016 to Sept, 2019]. Performed patient processing on VISTA and CPRS systems: [Feb, 1999 to present]. Manages local area network and WIFI network IT infrastructure for allowing or denying access to WIFI network by tenants: [Home Lab] [Aug, 2021 to present]. Setup network printer/scanner to provide printing and scanning services to all desktop computers and server computers on Local Area Network (LAN). Network printer/scanner also provide services to 8 Linux Virtual Servers and one bare-metal Windows 2019 server. Performed all aspects of Clinical Laboratory Functions, such as performing lab testing in the Chemistry, Hematology, Microbiology, and Blood Bank department: [VAMC Northport] [Dec, 2003 to present].[Performed Clinical Laboratory Scientist duties in Clinical Chemistry, Hematology, and Microbiology]:[Northwell] [Jan, 2016 - Sept, 2019].EDUCATIONMasters degree in Data Science and Analytics in progress at Eastern University, ST. Davids, PA: [August 2003 - current]Data Science & Machine Learning: Making Data-Driven Decision MIT Certificate: [Feb 2023] Applied Data Science Program Certificate by MIT Professional Education: [June 2023] Clinical Laboratory Technologist License Number 012490: [Current to 10/31/2024] Professional Achievement in Clinical Laboratory Sciences: [June 27, 2003] Bachelor of Science Degree, Stony Brook University: [June 30, 2003] Technical Support Fundamentals: [May 6, 2021]Systems Administration and IT Infrastructure Services: [May 31, 2021] The Bits and Bytes of Computer Networking: [July 6, 2021] Google IT Support Professional Certificate: [Oct 9, 2021] Introduction to C Programming Variable Input Output: [Aug 8, 2022] IT Security Defense against the digital dark arts: [Sept 6, 2021] Operating System and You: Becoming a Power User: [Oct 9, 2021] TECHNICAL & BUSINESS PROFICIENCIESTechnical:[Performed system administration, cyber security, and network monitoring duties on Linux Ubuntu servers and Windows server 2019 and Windows 10: troubleshooting server, troubleshooting network. Created and Managed user accounts access and authentication on Ubuntu server and Thunderbird email client on Ubuntu server.Managed cybersecurity on network at Home Lab.Worked with databases, such as MongoDB (No-SQL), MariaDB, SQL, and Postgres. Setup Windows and Linux virtual machines on Linux and setup Linux Ubuntu server on Windows server 2019 and Windows 10 (WSL2 and Linux).Performed Clinical Laboratory Scientist duties in Clinical Chemistry, Hematology, Blood Bank, and performed Covid-19 Testing in Microbiology.Performed Clinical Laboratory Scientist duties in Clinical Chemistry, Hematology, and Microbiology.] Business:[Performed project management and process improvement duties while developing Diagnosischeck.com web application, and IT infrastructure for hosting Diagnosischeck.com web application at Home Lab. Performed IT network engineering, system administration, and cybersecurity duties in maintaining the integrity of IT network used for hosting Diagnosischeck.com web application at Home Lab. Performed Microsoft Windows and Linux Network Management duties.] PROJECTSBuilt Tensorflow-GPU python virtual environments with CUDA, CUDNN support system for AI, Deep Learning, Neural Network Application Development and built PostgreSQL databases for all applications developed; used Spyder IDE, Jupyter Notebook and Anaconda-Navigator, August 2023. Built Image Recognition Deep Learning Malaria Detection AI application to predict malaria infection, June 2023.Developed both web and Desktop applications from scratch using Python, June, 2020. Built a presidential prediction application using the Python programming language, July 2020. Built computer trading software applications using the Python programming language, June 2021. Built an IT Infrastructure Home Lab for self-hosting a personally-built Python-based web application, called Diagnosischeck.com, Sep 2020.Built a Desktop Financial Market Prediction Software Application in C Programming Language, July 2022. ADDITIONAL SKILLS Sports writer at Bleacher Report. Creative writer and moderator at Mstardom Finance and Diagnosischeck.com. Built, wrote, host, and produced Economic Forecast and Financial News videos on YouTube. |
