Will Pak

Results-driven data scientist with a unique blend of expertise in competitive programming, optimization, algorithms, and data structures. With over a decade of experience, I excel in leveraging core programming languages and machine learning frameworks to solve complex problems. My passion lies in data acquisition, preprocessing, cleaning, visualization, feature engineering, and post-processing, enabling me to deliver exceptional insights and actionable solutions.

Experience:
• Developed and deployed a customer conversion rate prediction model using scikit-learn, employing optimization algorithms for efficient and accurate results.
• Implemented an AWS-based natural language processing pipeline for sentiment analysis using PyTorch, optimizing performance by leveraging advanced data structures.
• Developed a recurrent deep learning model using TensorFlow and Matlab Neural Network Toolbox to detect sleep patterns from EEG/ECG data.
• Built a heart rate monitoring system using PyTorch and Android Studio, leveraging various data structures for efficient data processing.
• Developed a life insurance classification model using transformers from Huggingface, enhancing the model's accuracy and efficiency.
• Created a predictive model for license plate detection using TensorFlow.

Services:
• Data Acquisition: Skilled in efficiently collecting data from physical devices, databases, and web sources, employing optimized algorithms and data structures.
• Data Cleaning and Preprocessing: Proficient in applying advanced techniques to clean, preprocess, visualize, and engineer features, ensuring high-quality data for analysis.
• ML/DL Models: Experienced in developing robust models for classification, clustering, and regression.
• Deployment: Well-versed in deploying products to AWS using efficient workflows with Git, Jira, and Jenkins, optimizing the deployment process for seamless integration.
• Natural Language Processing: Extensive experience working with large language models based on transformers.