Charles Young

Analytic scientist with 7 years of experience building and deploying statistical and machine learning models to drive insights and improve system performance. Skilled in Python, R and MATLAB for developing mathematical models that have enhanced efficiency and reduced latency. Collaborative communicator adept at translating complex analyses into compelling data visualizations and strategies for cross-functional stakeholders.

Research Scientist (Mathematics) - Lockheed Martin Corporation - Dayton, OH

(2023-06)

• Develops mathematical models using statistical modeling and research methods for optimizing aerospace systems, achieving a 15% increase in efficiency.
• Collaborates with cross-functional teams to apply number theory in cryptographic systems for secure communications.
• Presents research findings with compelling data visualizations at international conferences, including the American Mathematical Society Annual Meeting.

Data Scientist - IBM - Research Triangle Park, NC

(2020-06 - 2023-05)

• Developed algorithms for predictive analytics in cloud computing infrastructure, writing complex SQL queries to extract and prepare data, achieving a 10% reduction in latency.
• Applied statistical modeling and machine learning techniques with quantitative judgment to analyze large datasets for enterprise clients.
• Led a team of four junior analysts in a project focused on optimizing supply chain logistics.

Teaching Assistant - University of Michigan - Ann Arbor, MI

(2018-08 - 2020-05)

• Taught undergraduate courses in Calculus II and Linear Algebra, achieving a student evaluation score of 4.8/5.0.
• Developed interactive lesson plans and problem sets to enhance student engagement.
• Mentored students in research projects, contributing to two co-authored conference papers.

Ph.D. - Mathematics - The Ohio State University (2025-05)

Master of Science - Mathematics - University of Michigan (2020-05)

Bachelor of Science - Mathematics - Case Western Reserve University (2018-05)