Data has become an essential element in the management (strategic or operational) of any companies, or administrations. It can take many forms, and be more
Our Management Team
Christophe Le Lannou
I studied Mathematics at the Ecole Polytechnique, and then Engineering at the Ecole Nationale Supérieure des Mines, both in Paris. I spent the first 17 years of my working career in the finance sector. In particular, for 5 of these years, I was head of quantitative research and trading at Carrousel Capital, a large London based hedge-fund. I also spent over a year as a mentor at the Cambridge Judge Business School, where I provided advice and support to young business ventures. At present, I am also an external lecturer at the Toulouse Business School on quantitative finance and data visualisation. I have also just recently co-written the course on Machine Learning for the CFA Level II. Founding dataLearning, and being the CEO since its creation in 2014, has been an exciting and enriching experience.
I carry out my passion for science as a professional mathematician. As a Professor at Université Côte d’Azur, I am affiliated with CNRS and Inria, leading institutes in mathematics, computer science, and AI. For more than 20 years, I have been involved in industrial projects, with partners such as the French Space Agency, EADS, Thalès, and more recently startups of the French Riviera ecosystem. My expertise is more particularly centered on optimisation and control, with a definite taste for geometric insights and computations.
I have been with dataLearning since its foundation as a mathematical expert. I create models and algorithms to efficiently solve large scale problems. My strong academic background means I am able to constantly be in touch with the newest research in machine learning.
Discover our world: our ethics, our team and community
We place people at the center of our business values.
Founded in London in 2014, dataLearning is an Advanced Analytics consulting firm, based both in the UK and France. By intertwining innovation, human ingenuity, and data intelligence, we partner with businesses to ensure their full potential in the digital era.
The ethical, technological, legal, and socio-economic aspects of Artificial Intelligence in business are of the utmost importance for dataLearning. We hold strong social corporate values which we place at the center of our actions, and missions, with our clients.
To give but one example, Artificial Intelligence algorithms are trained using historical datasets. These are likely to be partially, or inherently biased. For this reason, we continuously adjust our algorithms to ensure they accurately represent reality.
We also audit the decisions of our autonomous systems to ensure we have ethical outputs which are in line with our social corporate values.
People are our greatest asset
The strong sense of community drives us to share, to go further, and to improve, by building off one another.
Our working environment nourishes collaboration, empathy, mentoring, and continuous learning.
A community of data experts
The Franco-British Data Society, founded in 2018, is a networking platform which gathers numerous backgrounds, from data experts, to lawyers, academics, start-ups, banking institutions, and government entities, to discuss all aspects of data. The FBDS’s actions and events promote cooperation on, and understanding of, data issues between France and the United Kingdom.
A community of partners
Our network of external partners, composed of leaders specialised in specific algorithms, specific technologies or experts driving change- processes in organisations, is continually pushing us to think further, in fresh and innovative ways.
Our latest blog posts
“Data, AI and The Built Environment: Women’s safety, buildings and the public, and managing waste” – Webinar November 09 2021
“Covid & AI: Unexpected challenges and solutions” : Webinar co-organised by the French Embassy, the Franco-British Data Society and the Inria London Programme – May 21 2021
Selon un article paru au Royaume-Uni, un sondage auprès d’une population d’environ mille data analysts montrait que plus de la moitié d’entre eux envisageaient de changer de travail en 2020.