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Andrew M

- Research Program Mentor

MA at University of California Berkeley (UC Berkeley)

Expertise

Data Science & Analytics

Bio

Accredited data scientist trained in modern mathematical modeling & machine learning methods with an academic background in statistics. Experienced in the industry of Energy & Commodities alongside business practices & methodologies associated with global Fortune 100 Companies. Interested in data science & machine applications to solve real-life & pragmatic problems. A portfolio of my work can be found at: statisticsAndrew.wordpress.com

Project ideas

Project ideas are meant to help inspire student thinking about their own project. Students are in the driver seat of their research and are free to use any or none of the ideas shared by their mentors.

Large Language Model Chatbots

Develop and deploy a chatbot powered by large language models (LLMs), such as OpenAI's GPT-4, to enhance customer service, streamline operations, and provide users with a more interactive and responsive experience. This AI-driven chatbot will be capable of understanding and generating human-like text based on user inputs, thereby providing relevant information, answering queries, and performing specific tasks autonomously.

NLP Sentiment Analysis

Develop a robust sentiment analysis model leveraging Natural Language Processing (NLP) techniques to automatically identify and categorize sentiments expressed in textual data. This model will be instrumental in analyzing customer feedback, social media interactions, and other text-based data sources to gain insights into public opinion, customer satisfaction, and overall sentiment trends.

Genetic Algorithms

Research and implement a Genetic Algorithm (GA) framework to solve complex optimization problems. Genetic Algorithms are a type of evolutionary/heuristic algorithm that mimic the process of natural selection to identify optimal or near-optimal solutions for various types of optimization challenges. This project will focus on applying GAs to specific optimization problems within our organization, such as resource allocation, scheduling, and route optimization.

Coding skills

Python, R, SQL

Teaching experience

Prior to Polygence, I have served as a Teaching Assistant and Curriculum Engineer for Data Science Bootcamps at edX as well as a Teaching Assistant for undergraduate statistics & data science courses at UC Berkeley.

Credentials

Work experience

World Fuel Services (2022 - Current)
Data Scientist

Education

University of California Santa Barbara (UCSB)
BS Bachelor of Science (2021)
Statistics
University of California Berkeley (UC Berkeley)
MA Master of Arts (2022)
Statistics

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