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Maths | Data/ML | Fullstack | Nix/NixOS

"Basically a wizard"

Employed at Tweag to build software for a data world

I'm a freelancer, contact me by email. Currently not available for freelance.

Experience

Albert School of Data

Sep 2023 - now: Lecturer

  • "Supervised Learning" (16h)
  • "Scraping and data cleaning" (10h)
  • "Handling spatial data" (4h)

Tweag, a Modus Create company

Sep 2023 - now: Senior Data & Software Engineering Consultant

  • integrate ML in a marketing solution
  • custom software integration (dev + ops)
  • leadership: coaching, project management
  • growth: hiring (interviews), marketing (speaker, blog editor), sales (solution design)

Sep 2021 - Sep 2023: Data & Software Engineering Consultant

  • scaffold Python monorepos (blog post)
  • distributed cloud computing for ML (dataloader backed by ray on Azure AKS)
  • native extension for Spark in Scala (github:kaiko.ai/spark-dicom)
  • analysis and processing of temporal geospatial data
  • speaker at PyConFr 2023: "Python moderne et fonctionnel pour des logiciels robustes" (video)

May 2020 - Oct 2020: Internship

Jan 2020 - Aug 2021: Data & Software Engineer

  • integrate with many third party data sources
  • manage ETL jobs, data freshness and data accuracy

Freelance

Jan 2020 - Aug 2020: Fullstack Software Engineer

Education

  • 2019-2020: Master "Data and Artificial Intelligence", Institut Polytechnique de Paris
  • 2016-2020: Ingénieur, Ecole des Ponts

Skills, technologies, opinions

data engineering

  • analytics (Hadoop MapReduce, Spark, Modern Data Stack)
  • cloud data lakehouse (Spark SQL, BigQuery, Snowflake, Athena)
  • parallel computing, distributed computing (Ray is cool)
  • data transformation pipelines need similar features than build systems

data science/ML

  • you've gotta love a good linear regression (or xgboost)
  • aren't Foundational Models just crushing the field?

software engineering

  • functional programming (Haskell, Scala)
  • apply FP ideas to other languages (Python, Rust, Java)
  • Inheritance is bad
  • Inheritance is bad, really
  • Domain Driven Design (DDD) is good
  • automated testing matters
  • aim for 100% automated deployement
  • technological success includes reproducibility (Nix ❤)

web applications

  • frontend: the Open Web Platform is the most stable, React is nice, experimenting with HTMX
  • backend: REST is good, GraphQL is nice to serve SPA data but it's not so simple to solve N+1 query problem

desktop application & mobile development

  • make a web app unless you have hard requirement on being offline

GuillaumeDesforges's github stats

Guillaume Desforges's Projects

act icon act

Run your GitHub Actions locally 🚀

fix-python icon fix-python

A simple CLI tool to allow you to use Python "normally" in NixOS

haskell-guide icon haskell-guide

A monorepo of multiple micro Haskell projects, often made for articles or demonstration

home-manager icon home-manager

Manage a user environment using Nix [maintainer=@rycee]

hs-rl icon hs-rl

A toy project for myself to learn Haskell and improve my knowledge in Reinforcement Learning

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