Data Analyst, Machine Learning Engineer


As a graduate student pursuing a Master's degree in Computer Science from Purdue University, I am passionate about applying machine learning and deep learning techniques to solve real-world problems. I have a solid foundation in Python, SQL, R, C++, and Julia programming languages. I am experienced in working with popular machine-learning libraries such as Pandas, Scikit-learn, Seaborn, PyTorch, Keras, and TensorFlow.

I have experience conducting research, having worked on projects such as predicting earthquake trends, surveying document databases, and developing a graph-based keyword extraction tool. I co-authored a conference paper on graph-based keyword extraction for Twitter data, which was published in Springer's Lecture Notes in Electrical Engineering.

I am skilled in various databases, including SQL, MySQL, BigQuery, and NoSQL, and I enjoy exploring and implementing new technologies to build robust and efficient systems.

With a solid academic background and a deep interest in machine learning and data science, I am excited about new opportunities to learn, grow, and contribute to the field.


A company that has a positive work environment, supportive colleagues, and a good work-life balance, that offers opportunities for professional development and growth. A job that aligns with my values, interests, and strengths and allows me to grow my skills in data science to become a better skilled professional.

Employment Preferences
  • Chicago, Illinois, United States
  • San Francisco, California, United States
  • Seattle, Washington, United States
  • New York City, New York, United States
  • Austin, Texas, United States
Expected Base Salary

**,000 USD

Academic Degree

Total Professional Experience

no experience

Startup Experience

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Big-Tech Companies

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Enterprise Experience

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