DAVID CHEN

Engineering Graduate specializing in AI and Data
Paris, FR.

About

Highly motivated Engineering Graduate specializing in Artificial Intelligence and Data, with hands-on experience in developing robust microservices architectures and machine learning solutions. Proven ability to optimize data processing pipelines, implement real-time fraud detection systems, and enhance web applications, demonstrated through internships and impactful projects. Eager to leverage expertise in Python, Java, Kafka, and Spark to drive innovative data-driven solutions and contribute to cutting-edge advancements.

Work

Artik Consulting
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Consultant (Internship)

Paris, Île-de-France, France

Summary

Spearheaded the "Webhook" project as a Consultant for Colissimo, focusing on real-time parcel tracking system development and API optimization, leveraging Java, Spring Boot, and Kafka.

Highlights

Contributed to a significant project overhaul, migrating the system to Spring Boot and implementing message mapping for multiple Kafka topics to enhance data flow efficiency.

Developed and integrated new back-end API features, improving system functionality and data processing capabilities for real-time parcel tracking.

Wrote comprehensive unit and integration tests using JUnit 5 and Mockito, ensuring code quality and system reliability for critical applications.

Participated actively in daily Scrum meetings, fostering agile development practices and effective team collaboration to meet project deadlines.

Supported the "Webhook" project, which successfully reduced daily API calls by 70% (from 5.9M to 1.7M) by enabling real-time status updates without direct server requests.

Participated in drafting a successful call for tenders response for ESCP, contributing to new business acquisition and strategic growth for Artik Consulting.

Completed internal training on Angular (front-end), Spring Boot (back-end), Kafka & Spark (data processing), and Elasticsearch & Kibana (analysis & visualization) to enhance technical skill set and project contributions.

Technilog
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Internship

Paris, Île-de-France, France

Summary

Developed a prototype web application demonstrating machine learning models for Technilog, enhancing product features and user experience using Python, Plotly Dash, and Git.

Highlights

Implemented advanced variable forecasting features within the application, accurately predicting future sensor values for enhanced predictive analytics capabilities.

Designed and developed an impact analysis module to effectively study relationships and influences between complex system variables, providing critical insights.

Developed an anomaly detection module based on an autoencoder and reconstruction error, enabling the identification of critical deviations in data streams.

Improved user experience through implementing robust authentication features and streamlining model update processes, enhancing application usability and security.

Contributed significantly to the development of a web application designed to showcase new features of Technilog's solutions, supporting product innovation and client engagement.

Education

École supérieure d'informatique, électronique, automatique (ESIEA)
Paris, Île-de-France, France

Engineering Degree, Master level

Artificial Intelligence and Data

Wrexham Glyndwr University
Wrexham, Wales, UK

Study Abroad Exchange Semester

General Studies

Languages

French
English

Certificates

Relational Database

Issued By

freeCodeCamp

JavaScript Algorithms and Data Structures

Issued By

freeCodeCamp

Data Analysis with Python

Issued By

freeCodeCamp

Skills

Programming Languages

Python, Java, JavaScript, R.

Python Libraries & Frameworks

Pytorch, Tensorflow, Plotly Dash, Pandas, Pyspark, Spring Boot, Angular.

Databases & Data Tools

SQL, PostgreSQL, Kafka, Elasticsearch, Kibana, Spark, Tableau.

DevOps & Cloud Tools

Docker, Git.

Machine Learning & AI

ML Models (Stacked), Anomaly Detection, Variable Forecasting, Incremental Learning, Active Learning, Affective Computing, Fraud Scoring.

Architecture & APIs

Microservices Architecture, REST API, Swagger, Webhooks.

Projects

Real-Time Banking Fraud Detection (Personal Project)

Summary

Designed and implemented a microservices architecture for real-time banking fraud detection using the IEEE-CIS Fraud Detection dataset, leveraging a comprehensive data processing and machine learning pipeline.

Affective Computing: Classifying Unconventional Emotions (Research Project)

Summary

Conducted a research project at ESIEA to develop a solution for incrementally classifying unconventional emotions, involving extensive literature review and model experimentation.