Raymond Duc - Senior Al Engineer

Raymond Duc

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Raymond Duc

4.8

Gender

Male

Main expertise

AI Data Scientists Machine Learning Data Python TensorFlow PyTorch AWS Azure Big Data Architects Cloud Deep Learning

Introduction

Raymond Duc is an accomplished Data Scientist and AI Engineer with over 6 years of experience in extracting, analyzing, and interpreting large datasets from various sources. He utilizes algorithmic, data mining, artificial intelligence, machine learning, and statistical tools to make data accessible and valuable to businesses. His passion lies in delivering crucial data insights through advanced analytical functions and sophisticated data retrieval methods. Raymond is adept at managing and monitoring data from multiple streams and possesses the ability to synthesize quantitative information while interacting effectively with colleagues and clients.

Project list

AI-Powered Retail Automation

Design and implement an advanced computer vision software solution aimed at revolutionizing the grocery retail sector. This system leverages AI-driven product identification to reduce checkout mistakes, decrease plastic packaging usage, and improve operational workflow. By enhancing the shopping experience, this initiative seeks to offer a quicker, more user-friendly, and eco-friendly retail journey for customers while promoting business growth for grocery retailers.

Develop and train generative AI models using frameworks such as TensorFlow and PyTorch. Implement various NLP tasks, including text classification, sentiment analysis, named entity recognition, and language translation, using generative AI models. Continuously monitor and optimize generative AI model performance to ensure high accuracy, efficiency, and scalability. Develop and implement data pipelines to collect, process, and analyze data from various sources.

Technologies: Python, TensorFlow, PyTorch, Generative Adversarial Networks, GCP

FLYER

FLYER is the first high-quality virtual interactive English testing platform for children. Learn more at https://www.flyer.vn/

Study existing database, data flow, and business. Clean and transform data, manipulate data for analysis and visualization. Create Google Data Studio dashboards for major performance metrics based on customer expectations. Design, develop, and optimize automatic scoring for writing tests. Design, develop, and optimize automatic scoring for speaking tests. Design, develop, and optimize automatic generation of images and quizzes for use as learning content.

Technologies: Azure, PostgreSQL, MongoDB, Python, Google Data Studio, Kafka, Spark (ML), TensorFlow, Scikit-learn, LLM, ChatGPT, Supervised Learning, Reinforcement Learning, Stable Diffusion, GAN

Healthcare Services Optimization Platform

The client is one of the largest healthcare services groups in Asia, offering world-class distribution, commercial solutions, patient care, clinic outreach, data analytics, pharmacy channels, and payor services to meet the growing healthcare needs in the region.

Study existing database, data flow, and business. Clean and transform data, manipulating it for analysis and visualization. Design, develop, and optimize an ML classification model for grouping merchant categories. Design, develop, and optimize automatic scoring for writing tests. Design, develop, and optimize an ML recommendation system for inventory optimization.

Technologies: PowerBI, Postgres, HANA, Azure Synapse, DAX, DAX Studio

INVETO

INVETO is an online data analysis platform powered by AI, tailored for investors. The platform offers products including cryptocurrencies, securities, and real estate. It combines AI and ML algorithms to provide recommendations on buying and selling, along with insights into trends and historical pricing.

Study existing database, data flow, and business Clean and transform data, manipulating it for analysis and visualization Apply big data solutions to solve current business problems Design, develop, and optimize an ML recommendation system for buy/sell decisions Design, develop, and optimize an ML stock news analyst and summary using ChatGPT

Technologies: NodeJS, PostgreSQL, TensorFlow, Kafka, AWS, Kubernetes, Docker, Scikit-learn, Python, Pytorch, Supervised Learning, ChatGPT

AlSuViet

AlSuViet serves as a knowledgeable advisor, enabling users to easily access historical information from credible sources by interacting with the chatbot. The platform also plays a significant role in digitizing documents, thus supporting the preservation of knowledge for future generations.

Study existing database, data flow, and business. Clean, transform, and manipulate data for analysis and visualization. Design, develop, and optimize an AI chatbot using local knowledge, utilizing Google PaLM v2. Analyze and implement training algorithms. Design, develop, and optimize a machine learning classification model to detect inappropriate messages and questions.

Technologies: AWS, PostgreSQL, Python, Apache Superset, Hadoop, TensorFlow, PyTorch, Scikit-learn, Supervised Learning

Gaspol

An exclusive automotive platform integrating sports and digital media for modern mobility needs.

Study existing database and data flow. Clean and transform data for analytics. Create Google Data Studio/Superset dashboards for major performance metrics, based on customer expectations. Migrate data from legacy system to new one. Fix various data bugs.

Technologies: PostgreSQL, Java, Google Data Studio, Apache Superset

VECA Recycling Platform

VECA is a startup based in Vietnam that offers a matching platform for users and waste dealers to facilitate the collection and recycling of rubbish.

Study the existing database and data flow. Clean and transform data for analytics. Create Google Data Studio views for major performance metrics, based on customer expectations.

Technologies: MySQL, Google Data Studio

Full-Scale Analysis of Reinforced Asphalt Pavement

The project involves the statistical analysis of mechanical measurements from a full-scale test on reinforced asphalt pavement. This analysis enhances the understanding of test outcomes and aids in assessing pavement performance effectively.

Statistical analysis of mechanical measurements during a full-scale test of reinforced asphalt pavement using Python. Collecting data and designing a dataset featuring significant characteristics of the pavement structure. Studying and interpreting the large dataset through Panel analysis, adhering to the CRISP-DM methodology.

Technologies: PostgreSQL, Python, Apache Superset, Azure

Taxi Trip Duration Prediction for New York City

The project focused on predicting the duration of taxi trips in New York City using statistical models. It involved analyzing mechanical measurements and understanding the factors affecting trip duration.

Predict duration of taxi trips in New York City. (Java, R) Solve the data mining problem using models (linear regression and artificial neural network) while following CRISP-DM methodology.

Technologies: PostgreSQL, Java, Google Data Studio, Apache Superset

Social Network User Profile Completion and Influencer Detection

In this project, we focused on a social network with numerous users, many of whom have incomplete profile information. The goal was to develop methods to fill these missing attributes and identify influencers, defined as users with extensive connections within the network.

The illusion of hidden personal data using Python. Fill incomplete profiles and find influencers in a network using community detection methods, such as hierarchical clustering, Louvain method, and simulated annealing, while following the CRISP-DM methodology.

Technologies: Azure, PostgreSQL, Python, Apache Superset

Project list

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