Identity fraud detection
Tasks : Design and development of a hybrid solution for identity fraud detection based on + Design and development of deep learning workflow for face matching to detect duplicates based on biometric data. + Design and development of machine learning workectflow to detect identity fraud based on demographic data. + Implementing expert-based approach and using predefined rules to cover other identity fraud scenarios. + Design and development of web application to deploy all models developed to capture different identity fraud scenarios. + Designing big data architecture to work on scalable environment and detect identity fraud cases in real time. Tools and techniques : Scikit-learn, Keras, Tensorflow, Open CV, Pandas, Spark, hadoop, Flask, HTML, CSS. Statistical modeling, ML, DL, NLP, Computer vision, Big data, ML API.
About Me
Hello, i am a Machine learning engineer | Passionate about AI, ML, DL | |Web developer | Enthusiastic learner. I love the process of collecting ,cleaning and analyzing data. My focus is to use data to design, develop machine learning models and use my software skills to deploy those models into production to solve a business problem or automate a process
$ 15 USD/hr
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