Data Scientist

Data Analytics Champaign, Illinois, United States

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Summary

As a Master's student in Statistics at the University of Illinois at Urbana Champaign, I have gained a strong foundation in statistical learning, deep learning, unsupervised learning, time series analysis, and mathematical statistics.
With my proficiency in programming languages like Python, SQL, and R, and data science libraries such as Pandas, NumPy, Scikit-learn, Pytorch, and Matplotlib, I am confident in my ability to analyze and model complex datasets. I have also gained experience with databases like MongoDB and MySQL, and have worked with tools such as Git, Tableau, and Microsoft Excel.
During my experience as a Data Science Intern at Digital Factory Inc, I improved the clustering algorithm by analyzing customer behaviors based on geolocation data combined with other attributes, and designed a geotagging web service using Amazon Lambda and MongoDB. As an Associate Data Scientist at Celebal Technologies, I developed a machine learning model to predict insurance leads with data consisting of 2000+ features and 100M+ records, and designed a pipeline for an image processing project to find damaged anodes in a metallurgy plant using OpenCV and Python libraries. I also built predictive models on Azure ML using XGBoost and Random Forest algorithms as a Data Analyst Intern at Celebal Technologies.

Expectations

In a new role I want that it challenges me to grow my technical skills, and hope that the company values teamwork and collaboration. I am looking for a company that values work-life balance and supports professional development opportunities, and these values will help me become a more productive and engaged employee.