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Ahmed Alrasheed

Senior Data Scientist | Solutions Development & Consulting at Mozn

Ahmed Alrasheed has a wealth of experience in data science and related fields. Ahmed began their career in 2013 as the Co-Founder of Arabs for Altruism, a volunteering club based in the Greater Boston Area. From 2016 to 2017, they worked as a Gas Processing Operation Engineer for Saudi Aramco. In 2017, they joined Mozn as a Senior Data Scientist and Data Scientist, where they led the ideation and development of the company's Data Potential Assessment (DELTA) process and Policy Simulation Engine (PSI). In 2018, they became a Data Science Instructor at General Assembly. In 2020, they joined a COVID-19 response team at SFDA - الجهة الطبية والدوائية as a Data Science Consultant and also worked as a Data Science Consultant for a Confidential Government. Currently, they are a Senior Data Scientist | Risk and FinCrime at Mozn and a Data Science Consultant at Artificial Links.

Ahmed Alrasheed has a diverse education history. In 2010, they attended the Aramco College Preparatory Program to study Chemistry. Ahmed then went on to earn a Bachelor's Degree in Chemical Engineering from Northeastern University in 2016. In 2019, they completed a MicroMasters in Data Science from UC San Diego. Ahmed has also obtained various certifications from UC San Diego, John Hopkins University, DeepLearning.AI, Neo4j, and Udemy. These certifications include Algorithms for NP-complete Problems, Graph Algorithms, Data Structures Fundamentals, Algorithmic Design and Techniques, Executive Data Science, Natural Language Processing with Classification and Vector Spaces, Neo4j Graph Data Science Certified, Neo4j 4.0 Certified, Big Data Analytics Using Spark, The Complete Web Developer in 2020: Zero to Mastery, Graph Analytics for Big Data, NVIDIA DLI Certificate - Fundamentals of Accelerated Data Science with RAPIDS, Neo4j Certified Professional, REST APIs with Flask and Python, Deep Learning Specialization, Sequence Models, Convolutional Neural Networks, Structuring Machine Learning Projects, Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization, and Neural Networks and Deep Learning.

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