Edoardo Barp, Developer in Luxembourg City, Luxembourg
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Edoardo Barp

Verified Expert  in Engineering

Data Scientist and Back-end Developer

Location
Luxembourg City, Luxembourg
Toptal Member Since
August 29, 2022

Edoardo is a highly accomplished data scientist with a robust background in software development, specializing in driving innovation through R&D projects, automation, and artificial intelligence. With a proven track record of successfully leading multiple early-stage startups, Edoardo possesses the unique ability to shepherd a project from conceptualization to seamless implementation.

Portfolio

LocalAssistant.AI
FastAPI, PostgreSQL, Google API, Google Cloud, Cloud, Python 3, React
Calensync.live
React, AWS CloudFront, AWS Lambda, Google API, Python, FastAPI, PostgreSQL...
Opali Analytics
Rust, Python 3, AWS Lambda, AWS CloudFormation, TypeScript, Webpack, Bootstrap...

Experience

Availability

Part-time

Preferred Environment

Linux, Python 3, Rust, Neo4j, PyCharm, Docker, Scikit-learn, PyTorch, Amazon Web Services (AWS), Apollo Server

The most amazing...

...project I've led, researched, and implemented is an ML-based solution capable of detecting shellcode cyberattacks in raw data at 5GB per second.

Work Experience

Founder

2023 - PRESENT
LocalAssistant.AI
  • Designed and developed a ChatGPT-like interface in React.
  • Integrated with OpenRouter.ai models to provide a wide array of choices.
  • Integrated the Paddle.com payment processor to buy a license easily.
Technologies: FastAPI, PostgreSQL, Google API, Google Cloud, Cloud, Python 3, React

Full-stack Developer

2023 - PRESENT
Calensync.live
  • Created both the front and back end of the website using React and Python/FastAPI.
  • Developed calendar syncing algorithm and integrated it with Google API and webhooks.
  • Integrated Paddle.com payment provider with a subscription mechanism.
Technologies: React, AWS CloudFront, AWS Lambda, Google API, Python, FastAPI, PostgreSQL, Paddle, API Development, Unit Testing, Pytest, Project Management

Founder

2023 - PRESENT
Opali Analytics
  • Designed a DynamoDB database to allow for extremely fast and affordable analytics events.
  • Developed a REST API in Python on AWS (Lambda, API Gateway) to handle all user-related requests: payments, website management, and dashboard.
  • Designed and developed a dashboard using Bootstrap and TypeScript.
  • Developed event handling in Rust to reduce latency.
Technologies: Rust, Python 3, AWS Lambda, AWS CloudFormation, TypeScript, Webpack, Bootstrap, Amazon DynamoDB, FastAPI, Full-stack, ChatGPT, API Development, Unit Testing, Pytest

Python Developer

2024 - 2024
Occam AI Inc.
  • Designed and implemented multiple integration tools into the automation framework, allowing the AI to interact with them.
  • Made several refactoring decisions to improve the framework, largely simplifying the development of the process.
  • Wrote unit tests for all integrated tools to avoid introducing bugs, which allowed for a seamless refactorization.
  • Benchmarked similar solutions and wrote a report on how to get the best edge against the competition.
  • Integrated multiple clients' LLM APIs to get the best LLM choice for the task automatically.
Technologies: Python, Machine Learning, Data Engineering, Large Language Models (LLMs)

Data Engineer and Scientist

2023 - 2023
NDA
  • Developed a data pipeline to fetch information from the Refinitive API and process it.
  • Created an analysis pipeline to track market anomalies and trigger alerts.
  • Scraped information about relevant company websites to create custom reports using GPT.
Technologies: Refinitive API, Python 3, Python, Pandas, Data Science, Data Visualization, Scraping, Generative Pre-trained Transformers (GPT), Unit Testing, Databricks, Pytest, Software QA

Neo4j Cypher Queries Developer

2023 - 2023
Public Defence
  • Took over an abandoned repository and updated all outdated protocols.
  • Wrote an optimal data pipeline to process 1 TB of data in less than a day (the previous version would have taken months).
  • Created complex data analysis Neo4j Cypher queries to detect fraudulent blockchain transactions.
  • Created complex Neo4j Cypher queries to follow a transaction money flow and provide analysis to prove the ownership of the receiving wallet.
Technologies: Neo4j, Cypher, Graph Databases, Python, Blockchain, Bitcoin, Data Science, Data Engineering, Software QA

Cloud and Neo4j Developer

2022 - 2023
Amara
  • Implemented multiple solidity smart contracts to handle auction mechanisms, sponsoring, and general NFT exchanges.
  • Built the containerized deployment process for Google Cloud Platform.
  • Implemented a social recommendation system for the users using graph theory and machine learning.
  • Implemented and maintained the Neo4j/GraphQL API, including writing multiple custom functions.
Technologies: Neo4j, GraphQL, Apollo Server, Node.js, Cypher, Docker, Google Cloud Platform (GCP), Solidity, API Integration, Web Servers, Cloud Deployment, OpenAI GPT-3 API, Software, Software Development, API Development, Data Engineering, Software QA

Chief Technology Officer

2020 - 2022
X80 Security
  • Created an API-based automated agent continuously extracting data from clients' sources, such as AWS, Azure, Google Cloud Platform, GitHub, and Google Workspace, into our storage awaiting processing.
  • Designed and implemented the graph structure on Neo4j to load clients' data, including infrastructure, assets, users, and permissions. It allowed the team to analyze complex relationships and find security flaws.
  • Outlined and developed a framework for the abovementioned graph, allowing developers and data scientists to easily extend the structure and add new analysis models for continuous improvement.
  • Created an automated vulnerability scanner running on clients' AWS and GCP clouds to analyze their instances and report any new issues continuously.
  • Managed the entire project, from ideation to a fully working production software deployed on multiple enterprise clients.
  • Designed a detailed roadmap with milestones and delegated internally, as well as externally, when needed. Oversaw the entire execution.
  • Designed systems to protect data with special compliance needs, such as HIPAA and GDPR. Developed a mechanism to detect potential leaks and prevent them from happening.
Technologies: Product Strategy, Competitive Strategy, Product Management, Data Science, Team Management, Graph Theory, Roadmaps, Neo4j, Python, REST APIs, AWS Lambda, Amazon Web Services (AWS), AWS CloudFormation, Architecture, Enterprise Systems, APIs, Web Development, GraphQL, Cypher, Airtable, Amazon CloudFront CDN, Linux Servers, NGINX, Amazon S3 (AWS S3), SQL, Amazon EC2, SaaS, B2B, GitHub, API Integration, Web Servers, Cloud Deployment, Azure, System Architecture, Software, CTO, Venture Funding, Venture Capital, Software Development, API Development, Data Engineering, Unit Testing, Abstract Syntax Trees (AST), Pytest, pylint, ANTLR, Code Review, Source Code Review, Software QA, Project Management

VP of Engineering

2019 - 2020
X80 Security
  • Researched and developed a machine-learning-based high-performance software in Rust capable of detecting shellcode cybersecurity threats in raw network data.
  • Containerized the solution using Docker to make it easily deployable on-premise.
  • Built the company's entire cloud infrastructure on AWS.
  • Managed tech roadmaps, assigned tasks, and mentored junior developers.
  • Closed contract with one of the largest French cybersecurity companies to develop a specific cyberattack detection software.
  • Set up Neo4j and PostgreSQL databases with automated backup and security rules.
  • Set up isolated environments, firewall security rules, and a REST API with AWS Lambdas.
  • Included several AWS services with proper deployment using CloudFormation, such as AWS Lambda, SQS, SNS, Secrets Manager, S3, REST API, RDS, and AWS IoT.
  • Designed and implemented the company's python codebase, and later on managed the development on it.
  • Developed RAM scanner in Rust in order to improve speed to 5 Gbit/s on the average laptop.
Technologies: Python 3, Rust, Docker, Kanban, Team Management, IT Project Management, Cybersecurity, Cloud Infrastructure, Neo4j, REST, Python, REST APIs, AWS Lambda, Amazon Web Services (AWS), AWS CloudFormation, Architecture, Enterprise Systems, APIs, Amazon DynamoDB, Jupyter, Web Development, GraphQL, Cypher, Airtable, Amazon CloudFront CDN, Linux Servers, NGINX, Amazon S3 (AWS S3), SQL, Amazon EC2, SaaS, B2B, GitHub, API Integration, Web Servers, Cloud Deployment, Azure, System Architecture, Software, CTO, Venture Funding, Venture Capital, Software Development, Retool, API Development, Data Engineering, Unit Testing, Abstract Syntax Trees (AST), Pytest, pylint, ANTLR, Code Review, Source Code Review, Software QA, Project Management, Cyberattacks

Data Scientist

2018 - 2019
Shift Technology
  • Implemented state-of-the-art models to detect and read car license plates in pictures.
  • Researched and implemented new detection algorithms for specific types of fraudulent Italian claims.
  • Provided technical explanations and support during sales meetings in Italy for potential clients.
  • Created a pipeline to process, load, and analyze several gigabytes of raw data daily from our clients.
Technologies: C#, Applied Research, Anomaly Detection, Machine Learning, Node.js, Enterprise Systems, Jupyter, Pandas, Web Scraping, Scraping, Video Streaming, SQL, Microsoft Excel, GitHub, Cloud Deployment, Software, Software Development, Refinitive API, Data Engineering, Software QA

Teacher Assistant

2018 - 2018
University of Warwick
  • Learned CUDA and developed simulations using it to demonstrate speed gain against CPU.
  • Taught students what a GPU is, what CUDA is, and when you should consider it.
  • Participated in the development of CUDA.jl, the Julia CUDA wrapper.
Technologies: GPU Computing, Graphics Processing Unit (GPU), Numerical Analysis, NVIDIA CUDA, Jupyter, Video Streaming, GitHub, Software, Software Development

Lead Back-end Developer

2015 - 2016
Frecibo
  • Set up the infrastructure made of a MySQL database and a Ubuntu server.
  • Set up CI/CD for continuous development and integration.
  • Designed and implemented the entire back-end logic.
  • Created a REST API to interact with the front and integrated the endpoints.
Technologies: PHP, Marketplaces, cPanel, Payment APIs, SQL, Django, GitHub, Web Servers, Salesforce API, Office 365 API, Software, Software Development

Research and Development of High-performance Shellcode Detector

A model capable of detecting shellcodes, a type of cybersecurity threat, in raw network data.

This project consisted of two large parts—researching a model for very high-speed inference and its implementation. Due to NDA, I can't go into any details about the research side. Still, the main issue I can comment on is that the model should have a high detection rate with a shallow false positive rate to ensure false positives wouldn't overwhelm the analysts.

One of the main project constraints was the speed since it acts as a firewall and, therefore, must make decisions to let packets go or not go through in real time. It was estimated that the solution would need to go at 1 GBps speed, at least, on an average laptop. Furthermore, the solution's security was also critical, which led me to use the Rust language that combines these two features. Data had to be processed and kept at the lowest levels of cache and use vectorization at the CPU level to reach the expected speed.

The final solution was able to reach 5GBps of an average laptop with a detection rate of over 95% and a false positive rate under 0.000000001%, which means one false positive per Terabyte of data.

Created MLJ.jl, Julia's Largest Machine Learning Framework

https://github.com/alan-turing-institute/MLJ.jl
As part of my master's degree, I realized there was a significant shortcoming in the ecosystem of Julia programming language—the absence of a unifying machine learning framework, alike scikit in Python.

I, therefore, designed, architected, and implemented the first version of that framework. The difficulty was designing a well-balanced interface, something generic enough to include all models but strict enough that it wouldn't be lengthy and too abstract to use.

By the end of my master's, a dozen of the most fundamental machine learning libraries had been unified, and the project had attracted the Alan Turing Institute's attention. I've been invited to present it at the Julia Convention and ended up taking it over and continuing to develop it ever since.

Creator and Owner of Websek.co

Websek.co is a simple SaaS tool to alert users about potential security issues and misconfigurations on their website.

I developed the whole project with the following stack and structure:
• A REST API used by the front end with AWS Lambda
• A scheduler to launch EC2 analysis instances when required using AWS Lambda and AWS EC2
• A monitoring agent to verify the instances are healthy with AWS Lambda
• An analysis tool based on OWASP ZAP
• A PostgreSQL database
• A simple Bootstrap and jQuery front end

Co-author of a Peer-reviewed Scientific Paper

I took responsibility for implementing and studying the random interchange loop model used to make a numerical analysis of quantum dynamics for ferromagnets.

The project consisted of a numerical model analysis to determine how various attributes change depending on environmental parameters. This environment exists on a 4D lattice—three space and one time dimensions— and gets more and more accurate as the lattice increases. From earlier research, the margin of error was acceptable, starting from around 100-lattice.

Before this paper, the only implementation of the model would take 10 minutes to simulate a 10-lattice. This is a minimal lattice that can't be accurately used for numerical analysis and would be too slow.

I redesigned and implemented the model in C, creating a software that could simulate a 160-lattice in a few seconds. With such a performance, we could do a grid search on multiple parameters, giving us a global view of how each parameter affects the results. The paper is a collection of the most important results and explains its further implications.

Invester: Stock Price Prediction Bot

https://github.com/dominusmi/Invester
A stock price prediction bot written in Julia.

Backstory: I was finishing my degree in mathematics, and having been interested for years in stock trading, I decided to try and write my trading agent. The idea was not to do real-time algo-trading but mostly mid-long-term suggestions.

Tech: I created a framework to allow for different trading strategies so that I could independently compare different ideas. I also implemented backtesting mechanisms and various strategies, some heavily reliant on machine learning while others followed simpler signals. The code was deployed to the cloud and would run daily, giving a list of the top 10 suggestions to buy.

Interesting observation: The more complex the algorithm was, the less well it handled the early COVID-19 period.

Twitter Sentiment Analysis

https://github.com/dominusmi/Twitter-Sentiment-Analysis-Project
A sentiment analysis classifier based on Tweets.

Designed, researched, and developed several classifiers to process and study tweets and predict the sentiment as either positive, negative, or neutral.

Train Ticket Cost Optimizer

A software to scrape train ticket providers to get notified when train tickets were at an advantageous price. The software would run daily and scrape data from multiple train ticket providers to find the best deal for a specific route, with specified constraints, such as time periods and number of station changes.
2017 - 2018

Master's Degree in Informatics and Applied Mathematics

University of Warwick - Warwick, United Kingdom

2014 - 2017

Bachelor's Degree in Mathematics and Physics

University of Warwick - Warwick, United Kingdom

Libraries/APIs

API Development, Scikit-learn, jQuery, Pandas, Refinitive API, PyTorch, REST APIs, Node.js, SQLAlchemy, Salesforce API, Office 365 API, React, Google API

Tools

AWS CloudFormation, Jupyter, GitHub, Pytest, Retool, pylint, PyCharm, Microsoft Excel, Amazon CloudFront CDN, NGINX, Wix, Webpack, ChatGPT, AWS CloudFront, ANTLR, AI Prompts

Languages

Python 3, Python, JavaScript, Cypher, Rust, HTML, CSS, SQL, Solidity, C#, Julia, C, Java, GraphQL, R, PHP, TypeScript

Paradigms

Data Science, Unit Testing, B2B, Anomaly Detection, Kanban, REST

Platforms

AWS Lambda, Amazon Web Services (AWS), Docker, Amazon EC2, Azure, Linux, NVIDIA CUDA, cPanel, Google Cloud Platform (GCP), Blockchain, Databricks

Storage

Neo4j, Cloud Deployment, PostgreSQL, Amazon DynamoDB, Amazon S3 (AWS S3), Graph Databases, Google Cloud

Industry Expertise

Cybersecurity, Project Management

Frameworks

Django, Bootstrap

Other

APIs, API Integration, Software, Software Development, Data Engineering, Machine Learning, Graph Theory, Algebra, Architecture, Web Scraping, Scraping, Linux Servers, Data Scraping, SaaS, Web Servers, OpenAI GPT-3 API, System Architecture, Abstract Syntax Trees (AST), Code Review, Source Code Review, Software QA, Large Language Models (LLMs), Amazon Augmented AI (Amazon A2I), Artificial Intelligence (AI), Statistics, Applied Research, Physics, Mathematics, Applied Mathematics, Game Theory, Reinforcement Learning, Bayesian Inference & Modeling, Scientific Computing, Team Management, IT Project Management, Cloud Infrastructure, Product Strategy, Competitive Strategy, Product Management, Roadmaps, Software Architecture, eBPF, Optimization, Enterprise Systems, GPU Computing, Graphics Processing Unit (GPU), Numerical Analysis, Bots, Web Development, Trading, Stock Trading, Natural Language Processing (NLP), Airtable, Apollo Server, Video Streaming, Marketplaces, Payment APIs, Data Analysis, Generative Pre-trained Transformers (GPT), CTO, Venture Funding, Venture Capital, FastAPI, Full-stack, Bitcoin, Paddle, Data Visualization, Cloud, Cyberattacks, AI Translation

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