Bonjour,

I am a freelance data scientist and machine learning engineer with full stack experience. Constantly on the lookout for new challenges, I enjoy applying his data science skills to a wide variety of industries.

My interest in technology was sparked by my brother who introduced me to website creation with resources such as OpenClassrooms when I was 13. On that day, unfortunately I did not suddenly become passionate about coding but I learnt that I could learn anything on my own by searching for the right resources on the web. As the saying goes: “give a man a fish and you feed him for a day; teach a man to fish and you feed him for a lifetime”. I would add the following: “teach a man how to learn anything by himself and you give him the world”.

At 14, I built a website to promote my mum’s paintings which was both the first time I completed a useful project and the first time I earnt some pocket money by coding. It gave me a sense of accomplishment and encouraged me to develop my programming skills. If you would like your teenager children to spend some time off TikTok and start coding their future, giving the right incentives may be the key to great achievements.

At 16 while attending high school, I completed Harvard’s online Introduction to Computer Science course by David J. Malan, an exceptionally well-taught module which convinced me to study computer science at university. In the age of online courses, I believe any high school student should take at least one university module online in the subject he or she is considering pursuing at university.

Thanks to these milestones, the following year I went on to study computer science at Imperial College London where I learnt the basics of software engineering as well as some logic, mathematics and algorithmic fundamentals. Working part-time at Blockhain.com at the same time helped me grow an interest for emerging technologies. In my final year, I specialised in AI and machine learning and wrote a masters thesis on the fascinating subject of adversarial machine learning: how to fool (deep learning based) AI? which contributed to a publication.

Given my emerging passion for machine learning and computer vision in particular, I joined Panakeia to create AI for cancer diagnosis in September 2019. Being one of the first employees, I had the chance to define part of the technology stack, lead interviews with candidates way more senior than me and have the excitement of improving models for good week after week. I also discovered the world of medicine, its science, shortcomings, challenges and regulations.

Following this first fulltime experience, I started a new challence by becoming a freelancer in 2021. This new way of working gives me more flexibility and paradoxally less stress as I know my career into my own hands and its future is mine to shape. I believe this way of working will become more and more prevalent in the coming years and I look forward to seeing this (r)evolution unfold. At the moment I am doing data sience for TotalEnergies for which I have been mostly working on predicting and detecting incidents on oil and gas rigs. Besides all the learnings about drilling as well as data science on tabular data, this experience enables me to better understand the ways of working in large corporations and their relationships with smaller entities.

I do not know what lies ahead but I would like to start sharing some knowledge about data science and machine learning…

PS: My greatest achievement is and always will be Flappy Sixte, go play it!