Ayush Shah
Instructional Aide @University Of Michigan - School Of Information
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WORK HISTORY
Instructional Aide @University Of Michigan - School Of Information
Ann Arbor, MI, US
Collaborate with faculty to develop and facilitate course materials, including preparing, grading, and offering feedback on assignments and examinations in data manipulation, based on established rubrics- Support in-class exercises to reinforce essential data manipulation concepts, helping students build proficiency in handling, analyzing, and interpreting data through hands-on activities- Organize and guide one-on-one and group sessions, fostering a supportive environment where students engage in practical problem-solving and enhance their skills in Python programming, mathematical reasoning, and data handling techniques.
EDUCATION
Veermata Jijabai Technological Institute (VJTI)
Bachelor of Technology - BTech, Electrical, Electronics and Communications Engineering
University of Michigan
Master of Science - MS, Big Data Analytics
ABOUT AYUSH SHAH
I am a Data Scientist and Machine Learning Engineer with a Master’s in Information (Data Science & Analytics) from the University of Michigan, graduated in 2025. My expertise spans end-to-end model development, data pipeline engineering, and advanced analytics, with applications in healthcare, fintech, and sports technology.In my recent role as a Machine Learning Engineer at Western Union, I focused on building scalable ML models and enhancing DevOps pipelines for financial risk evaluation. Previously, as a Data Analyst Intern at Michigan Medicine, I developed predictive models for patient flow and ER triage operations that optimized resource allocation and reduced wait times. Earlier in my career at Telstra as a Senior Associate Software Engineer, I engineered large-scale data solutions to improve customer retention and system scalability using Spark, AWS, and SQL.Beyond professional roles, I have led research projects in sports analytics and machine learning, including penalty kick direction prediction using YOLO + LSTM pipelines and outcome forecasting models leveraging historical match data. These projects reflect my ability to blend technical depth with domain expertise to deliver strategic insights.With a strong foundation in Electronics and Communication (VJTI) and leadership experience in academic and research settings, I bring a methodical, collaborative, and impact-driven approach to solving complex data problems. I am eager to contribute to innovative teams tackling high-value challenges in data science, machine learning, and business analytics in 2025.
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