Machine Learning Data Science

Florian Charles

347-***-**** ad2cle@r.postjobfree.com https://github.com/Flo03

Education

A.S IN COMPUTER SCIENCE (4.0 GPA)

Borough Of Manhattan Community College, Manhattan, NYC Expected June 2024 and joining a 4-

year College in Fall 2024

• Honors and activities: Programing Club (President), Phi Theta Kappa member, The National Society of Leadership and Success Member, Dean’s list, New York Public Interest Research Group member

• Relevant courses: Discrete Structure & Applic Comp Sci, Calculus 1 & 2, Adv Programming Tech (Honors), Fund. of Computer Systems, University Physics 2, Macroeconomics

Break Through Tech AI New York

Cornell Tech, Certificate in Machine Learning/AI

Manhattan, NY

August 2023 – May 2024

• Develop statistical models, and utilize machine learning algorithms such as logistic regression, and decision trees.

• Perform feature engineering by transforming raw data into features that can be used by ML algorithms.

• Write complex, high-quality, well-documented Python code for ML tasks. Awards

• Won 1st Place @BMCC's hackathon (Fall-2022) & 2nd place (Fall-2023)

• Finalist in the National Science Foundation (NSF) Community College Innovation Challenge (2023)

• Won 1st Place in the 2023 American Bar Association Datafest (2023) Skills

• Languages: Intermediate Python, Intermediate C++, Intermediate SQL, HTML, CSS

• Programming tools: GitHub, Figma, Terminal, PyCharm, Cliona, Jupiter Notebook, Power BI, Excel, PowerPoint Experience

MENTOR

Impact Peer Mentor and Data Team

Manhattan, NY

February 2023 – Present

• Mentorship: Cultivate meaningful connections with 4+ mentees every semester, offering personalized guidance and leveraging my own experiences to provide valuable insights and support.

• Academic Support: Coach students in developing effective study techniques, time management skills, and optimal academic strategies, resulting in a measurable improvement in their academic performance.

• Data Analysis: Successfully cleaned and enhanced extensive datasets, uncovering actionable insights that led to a 15% reduction in program inefficiencies and a 10% boost in student engagement. Projects

House Price prediction model, (Python, PyCharm, Google Collab) Project Overview: Developed a sophisticated machine learning-based house price prediction model. This project involved extensive data analysis and application of predictive modeling to forecast real estate prices.

• Model Development: Designed and implemented the model using Python, focusing on leveraging advanced machine learning techniques for accurate real estate price forecasting.

• Data Processing: Employed advanced data processing methods for cleaning, sorting, and analysis and integrated multiple external data sources to enhance the model's predictive capabilities.

• Algorithm Implementation: Utilized a mix of machine learning algorithms, including logistic regression, decision trees, and k-nearest neighbors, to ensure precision and reliability in predictions. Credit score predicting model (Python, Machine Learning, Advanced Data Analytics, Agile Teamwork)

• Project Synopsis: In a dynamic team of five in addition to the help of our Accenture professionals, we engineered a sophisticated model Credit Score Analysis system, capitalizing on cutting-edge machine learning and deep data science methodologies.

• Collaborative Development: Engaged in an agile, cross-functional team environment, contributing to various stages of the project lifecycle, from conception to deployment, to deliver an innovative and high-impact data science solution.

• Project Impact: The goal of the initiative is to help determine who is worthy of getting loans which reduced the time taken by an individual to review the information.

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