Senior Data Scientist2018 - PRESENTFreelance
Technologies: Amazon Web Services (AWS), OpenCV, NLTK, Keras, Computer Vision, Data Analyst, TensorFlow, Data Science, Git, Jupyter, Pandas, AWS, Machine Learning, Technical Writing, Generative Adversarial Networks (GANs), Business Process Optimization, Natural Language Processing (NLP), Artificial Intelligence (AI), Deep Learning, Tableau, R, Python
- Developed a program that takes a lung CT scan as an input and gives back numerical and visualization output of detected nodules in the scan, along with malignancy score, on the nodule level and patient level.
- Developed a haircut and eyelashes recommendation system based on facial features and eye features; extended it to generate the photo of a human with the recommended changes, using GANs.
- Developed a receipt OCR and text classifier to categorize the items inside the receipt to various classes.
- Implemented a community detection algorithm, for academic purposes, to detect better design patterns for the UK railway stations.
- Designed and built a tremor classification model based on 3D gyroscope acceleration readings.
- Developed a snoring detection program built for medical purposes, this was built on AWS Sagemaker.
- Built an ace percentage forecast model to forecast the number of aces that will be made by a player in ATP or WTP; it reached 0.4 total loss in it.
- Developed a resume parser in Spanish and English, trained and deployed using AWS instances.
- Developed a sentiment scoring model based on restaurant reviews (Yelp dataset).
- Developed the RL agent based on Deep Q-Learning, to play Sichuan mahjong, along with creating a rule-based model to generate data acting as a start point performance, used SL to train on the generated data, and then RL to enhance the performance.
Data Scientist2018 - 2019Synapse Analytics
Technologies: OpenCV, Keras, Data Analyst, TensorFlow, Data Science, Git, Jupyter, Pandas, Machine Learning, Data Analysis, Data Visualization, Natural Language Processing (NLP), Computer Vision, Deep Learning, Tableau, R, Python
- Developed a cement market price daily forecasting, for a big cement firm, to reduce the loss of money between company and distributors, with ten days horizon; 91% of forecast values were within a 5% error margin.
- Implemented a store assortment forecast to forecast the weekly demand of products and give the best combination of products to get the highest revenue possible; 90% of forecasts were within a 5% error margin. Built on an AWS EC2 cloud instance.
- Developed a lot of presentations and dashboards for various projects using Superset, Tableau, and plotly.
- Handled big databases, and maintained its structure, design, and data flow.
- Worked on a clinic recommendation system, along with a time series forecasting model to predict when will be the next visit for a patient.