Hamid O.

Highly proficient Computer System Designers, Analysts and Software Engineering experts; R&D specialists with over 10 years of experience in software development, machine learning, modelling and analytics as well as web and cloud development for high scale and volume pull-through applications. --- o Developed, tested, and deployed Genetic Algorithm Optimisation model o Machine Learning to auto categorise products procured from external suppliers to optimise data, cost and list of suppliers. o unsupervised learning to identify saving opportunities for similar ingredients across multiple suppliers for food catering business. o created an automated data ingestion, processing and visualisation in Tableau o Developed Machine Learning solutions to optimise information management, business operations, information governance, compliance and quality control. Actively worked as part of regional team to design and develop solutions for the business. o Created an unsupervised Machine Learning pipeline to Identify and migrate 1000s of daily reports worth around £30K per report, saving millions of pounds in operational costs; -Transforming key information from daily reports into a Database, created a Language and Time Series Analytics capability using NLP and visualised in PowerBI, -Developed Image enhancements algorithms to improve OCR capabilities for legacy scanned documents - deployed ML models and APIs on Azure Platform using Flask API o WATCHME project: performance recommendation system In addition to numerical processing using time series and linear regression models, Advanced Bayesian statistics and Natural language Processing were used to provide suitable feedback to students and teachers. o SciCafe 2.0 project: created predictive data models to improve interactions of Social Networking Platform using Natural Language Processing, Named Entity Recognition and Sentiment Analysis; Interest matching system was used to recommend people and information through the platform. o VIDEOSENSE project: Developed video analytics techniques to preserve privacy through deep learning and predictive models o CORBYS project: Created a time-series algorithm to monitor, model and predict human walking gaits using sensor data from EMG, EEG, ECG and Encoders data to provide real-time feedback for gait correction of stroke patients. Machine Learning was used for the recommendation engine. o Designed, developed and delivered cloud projects for commercial companies worldwide as a freelancer. • Bespoke Web Application Development (Python, Angular, Node, HTML, PHP, CSS, JS) • Big Data Analytics, dashboards and visualisation in AWS and Azure platforms • 100+ freelance projects in UK, USA, Australia and Canada