Seasoned Data Scientist at IBM specializing in full-stack development, machine learning, and data analytics. Highly adaptable with a relentless drive for continual learning and skill refinement. Known for dedicating pers…
Seasoned Data Scientist at IBM specializing in full-stack development, machine learning, and data analytics. Highly adaptable with a relentless drive for continual learning and skill refinement. Known for dedicating personal time to mastering the craft and expanding capabilities. Seeking a challenging role within a visionary team to tackle complex problems, contribute expertise, and inspire innovative solutions. Holds a bachelor's degree in computer information systems from Lander University, focusing on software engineering. Enthusiastic about working in a technology-centric environment, especially in the field of machine learning.
Manage Big Data Applications for global network traffic analysis. Works with Python, JavaScript, Machine Learning, Pandas, Numpy, Docker, etc. Looking for senior machine learning engineer or data science role.
Serving as a Data Scientist on IBM's Research Triangle Park Global Networking team.
Leading the offering ownership of Data Analytics and Automated Configurations, focusing on crafting and executing data analytics solutions and automating configuration processes.
Developing and sustaining big data applications and interactive web dashboards that bolster data-driven decision-making and device management for network engineers at IBM and AT&T.
Pioneered advanced analytics and machine learning techniques on network data to foresee anomalies and potential security risks in networking traffic.
Automated network device configurations across IBM's global sites using Python, Ansible, Red Hat AAP, Kubernetes, and Docker, resulting in an 85% reduction in configuration time and a threefold boost in network deployment efficiency.
Established a change management system for logging and ticketing network configuration changes, significantly improving transparency, accountability, and traceability in network change processes.
Managed the creation of bespoke data anonymizing software for Lander University's administrative systems.
Engineered a secure data-sharing tool for cross-departmental use and student researchers, ensuring the confidentiality of sensitive information.
Led the development of a machine learning model to predict student retention rates at Lander University.
Designed interactive data visualizations using Microsoft's PowerBI to translate complex datasets into comprehensible insights.
Delivered a standalone application that gave Lander University administrators critical insights to enhance student support and engagement initiatives.
Equipped decision-makers with clear, actionable insights through compelling data visualizations, leading to informed strategic choices.
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