Dedicated Data Engineer with proven proficiency in Java 8 and Python, as well as expertise in NumPy, SciPy, Scikit-Learn, Pandas, Matplotlib, Jinja2, Selenium. Versed in programming, data computing, research design, and data analysis, implementing action-oriented solutions to business problems. Experienced with Big Data Modelling, Computer Vision, Integration, and Analysis, including the Hadoop ecosystem and Spark. Dealt successfully with high-impact situations at Amazon and worked extensively with various AWS products such as Amplify, Sagemaker, DynamoDB, S3, EMR, Data Pipeline, Lex, Lambda. Extremely engaged in Artificial Intelligence, with a significant portion of university and work projects being in this area.
Worked on the development of a startup platform providing free online Therapy and Psychiatry to eligible Medicaid patients.
Built the platform on the patient as well as the clinician side. Some features I've worked on include appointment scheduling, video calling, note taking, and more.
Worked on data analytics projects, web scraping, and solved sophisticated company-wide challenges using different disciplines of AI such as NLP and ML.
Managed AI development and production infrastructure for different companies.
Built AI models from scratch, creating and deploying machine learning algorithms.
Developed software solutions for storage and access of Petabyte scale data used for demand forecasting in SCOT. Configured and visited various warehouses to launch them into production.
Used advanced Java (lambdas, streams, parallel computing) to implement services from scratch to provide record-level results from databases in a specified format.
Implemented extensive automated testing for all code written to ensure the high quality results. Implemented algorithm responsible for package sorting and sorter lane load balancing in Amazon Warehouses around the world.
Designed, implemented, and tested an automatic email notification software program in Python that collects and reports donation metrics to charities associated with AmazonSmile. Followed Scrum methodology throughout the project.
Extracted data from Data Warehouse for processing, using technology such as Matplotlib to visualize it in the form of customizable graphs.
Closely collaborated with specialists to deliver a high-quality customer-facing product.
The project involved the implementation of Computer Vision algorithms in order to track the different shots, faces, and gender of people appearing in a video, split into frames. For shot detection, I used the Sum of Squared differences between two consecutive images, where the value would be big if those images contained very different content. For face detection, I used Open CV’s Haar Cascades detector, and for the gender classification, I trained a neural network with one hidden layer and logistic output on grayscale images of men and women. Acted as a Sole developer for the project and managed to complete the task with a high level of accuracy. Technologies and software used in the project: Computer Vision, Python, Open CV, Neural networks.
Developed a chatbot for a company hackathon that would pull data from the company API based on interactions with a customer using Facebook Messenger. The back-end code was implemented using serverless AWS Lambda and S3 was used for storing the code and graph plots produced in real-time as per customer interaction. The NLP in the chatbot was powered by AWS Lex. Worked as a Sole Developer for the project, developing the entire architecture. The project was successfully utilized during the hackathon. Technologies used in the project: Facebook Messenger API, AWS Lex, AWS Lambda, AWS S3.
Developed a React Native application from scratch that would run on both Android and iOS devices. It was built using AWS Amplify framework, which allows easy plugging of different components like AWS Cognito for authorization, AWS S3 for storage, etc. The app is working with a BLE device that sends data captured by sensors. This data is processed and shown in form of graphs on the app, as well as backed up to the Cloud. Acted as Sole Developer for the project, delivering the entire architecture and implementation. Built a scalable and modular application that is currently under development and expected to be launched soon. Technologies used in the project: React Native, AWS Amplify, AWS S3, AWS Cognito.
Education
Honours BSc. in Computer Science
University of Toronto
2013 - 2016 (3 years)
Bachelor of Technology, Computer Science and Engineering
