Lead data scientist at Implicity.

I'm a data scientist and ML engineer at Renault, working on putting our ML models into production.

I have been working as a Data Scientist at Renault Digital for 3 years, focusing on applications for the industry and manufacturing of electric cars. More recently, I became involved in the development of a MLOPS pipeline for Renault, and started to act as a relay with the DevOps team. Finally, I also contribute to the development Data Science best-practices with dedicated mentoring sessions.

Alonso Silva is currently a Researcher on Verifiable AI at Nokia Bell Labs in the Machine Learning and Systems Research Lab. He has previously worked at Safran in the Department of Mathematics and Temporal Data, in the Department of Electrical Engineering and Computer Sciences at the University of California, Berkeley, working with Professor Jean Walrand, at INRIA Paris Rocquencourt working with Dr. Philippe Jacquet and as a Research Consultant/Intern at Bell Labs Headquarters in Murray Hill, New Jersey, working with Dr. Iraj Saniee. He did his Ph.D. at INRIA Sophia-Antipolis under the direction of Dr. Eitan Altman. He obtained his Ph.D. degree in Physics from the École Supérieure d'Électricité in June 2010.

Alyssa helps lead Bloomberg’s Open Source Program Office (OSPO) in the Office of the CTO. Bloomberg's OSPO serves as the center of excellence for Bloomberg’s consumption of open source software and engagement with the broader open source community. When not helping define open source strategies and implementing partnerships and best practices, she is typically cycling to a mountaintop... or sleeping after having done so.

Andro Sabashvili transitioned to a data science career after obtaining a PhD in theoretical physics. Andro's data science journey commenced at Bank of Georgia, where he sharpened his skills in developing end-to-end machine learning projects, such as credit risk, propensity, and churn models using advanced machine learning algorithms. After designing a novel algorithm to automate the hyperparameter optimization process, which is currently patent-pending, he joined the startup company Dressler Consulting, where he led a team of data scientists building an automated machine learning platform. In his current role as a Staff Data Scientist at Majid Al Futtaim, Andro is focused on scaling up sales forecasting for thousands of stores, marketing mix modeling, marketing campaign impact estimation, and customer segmentation.

I completed my PhD in deep learning based time series forecasting in 2023 with the Karlsruhe Institute of Technology. In sktime, I am focusing on forecasting methods (mainly deep learning based ones) and implementing pipelines.

Benoît Courty is a data scientist with over 20 years of experience in the tech industry. He began his career as an inside subcontractor at a large French company, where he worked on a variety of projects. In 2015, he co-founded a UAV startup that developed technology to automatically fly around buildings to detect cracks. He then worked as a freelance data scientist for banking and TV companies. Three years ago, he became an internal data scientist at the French National Assembly. He is also a member of Data For Good France, where he discovered CodeCarbon in 2020 and became its main contributor.

I am an astronomical data scientist at the Space Telescope Science Institute in Baltimore. I work with a team on software engineers to develop a suite of open source tools to visualize and analyze data from the James Webb Space Telescope. I am especially interested in bringing these tools to the wider community and non-scientists who wonder about the Universe.

Senior data scientist at HelloWork

After having a career in Data Scientist and Developer Relations, Cheuk dedicated her work to the open-source community and founded CMD Limes, a Python consultants cooperation. She has also co-founded Humble Data, a beginner Python workshop that has been happening around the world. She has served the EuroPython Society board for two years and is now a fellow and director of the Python Software Foundation.

Open Source Software Engineer at Posit PBC (https://posit.co/). Working remotely from France.
Proudly focusing on Quarto (https://quarto.org/) - an open-source scientific and technical publishing system.

After 8 years of restricting datascientist because of my role in cybersecurity, I changed direction to empower them instead.

David Brochart is a Technical Director at QuantStack. David is a contributor to the Jupyter ecosystem. He focuses on the backend, mostly developing collaborative editing. He is also the main author of Jupyverse, a next-generation Jupyter server.

Devpriya Dave is a software engineer on the FX Options team at Bloomberg. While at Georgia Tech obtaining her master's degree, she helped design and build the system behind Georgia Tech's Machine Learning for Trading online course (https://www.udacity.com/course/machine-learning-for-trading--ud501). She is passionate about STEM mentorship and is always looking for ways to give back. In her free time, she enjoys reading books with a cup of coffee.

Engineer by education, Data Scientist by choice, researcher and lecturer by passion.

Emanuele earned his PhD in AI by researching time series forecasting in the energy field. He was a guest researcher at EPFL Lausanne, and he's now the Head of AI at xtream, where he solves business problems with AI.

He published 8 papers in international journals, presented and organized tracks and workshops at international conferences, including AMLD Lausanne, ODSC London, WeAreDevelopers Berlin, PyCon Florence, and lectured in Italy, Switzerland, and Poland.

Erik Welch is a senior system software engineer on the RAPIDS cuGraph team at NVIDIA and a core NetworkX developer. He has 20 years' experience using Python as a scientist, engineer, and open-source developer on a wide range of data and high-performance computing problems. He primarily works on nx-cugraph, an accelerated backend to NetworkX, and is the primary maintainer of the popular toolz library.

Francesc is a MSc Data Science student at ETH Zürich. Before that, he graduated in Maths & CS at the Polytechnic University of Catalonia (UPC) with a year abroad at Columbia University. He joined QuantCo as an intern in February 2024 to work on causal inference and its applications to insurance and fraud detection.

Data Scientist @ xtream

Senior Software Engineering at Modus Create with an academic background in mathematics, statistics and AI and professional experience in data engineering at scale. Leads the Data Engineering Technical Group of Modus Create's OSPO.

Guillaume is an open-source software engineer working at :probabl. He is a core maintainer of the scikit-learn and imbalanced-learn libraries.

Hendrik Makait is a data and software engineer building systems at the intersection of large-scale data management and machine learning. Currently, he works as an Open Source Engineer at Coiled, maintaining and improving Dask and its distributed execution engine. His focus areas include P2P shuffling, which allows shuffling large data at constant memory, and observability with Dask to help users understand and optimize their workloads.

Ian is a Scientific Software Developer at QuantStack working in the Jupyter ecosystem on JupyterLite and kernels. He is also a core maintainer of Matplotlib, Bokeh and ContourPy. Ian is British and drinks lots of tea.

Iisakki Rotko is a Software Engineer at Widgetti, where he focuses on advancing Python frameworks for complex dashboard creation through his work on Solara. With a background in theoretical physics from the University of Groningen, Iisakki combines his analytical skills with knowledge of Python and TypeScript to develop innovative tools at the interface between data and users, within the Jupyter ecosystem and beyond.

BSc in Information Technology and PhD in Bioinformatics from the Federal University of Rio Grande do Norte (UFRN). Currently, I am Postdoctoral Researcher at Institut Curie. During my academic journey, I have been extensively involved in research projects focusing on bioinformatics and data analysis. Pythonist and headbanger, with 6 years of experience in employing the Python data science and machine learning stack on bioinformatics and personal projects.

Software engineer on the team that develops Jdaviz.

Johan Mabille is a Technical Director specialized in high-performance computing in C++. He holds master's degree in computer science from Centrale-Supelec.

As an open source developer, Johan co-authored xtensor, xeus, and xsimd. He is also involved in the development of mamba. Prior to joining QuantStack, Johan was a quant developer at HSBC.

Johannes Bechberger is a JVM developer working on profilers and their underlying technology in the SapMachine team at SAP. He started at SAP in 2022 after two years of research studies at the KIT in Java security analyses. His work today comprises many open-source contributions and his blog, where he writes regularly on in-depth profiling and debugging topics and works on his JEP Candidate 435 to add a new profiling API to the OpenJDK. He has been an avid Python user for almost 10 years, with a special interest in type systems and debuggers.
Since 2023 he's touring through the meet-ups and conferences of Europe, like JavaZone and Devoxx Belgium to speak on various topics.

I am a core contributor to pandas and Apache Arrow, and a maintainer of GeoPandas. I did a PhD at Ghent University and VITO in air quality research and worked at the Paris-Saclay Center for Data Science. Currently, I work at Voltron Data, contributing to Apache Arrow, and am a freelance teacher of python (pandas) at Ghent University.

I am the lead devlopper of Onyxia Datalab and the creator of a set of open source libraries like Keycloakify, tss-react or Denoify.

Julien is a Scientific Software Engineer at QuantStack. He holds a MSc. Computer Science & Engineering from Université de Technologie de Compiègne and a MSc. Applied Mathematics, Computer Vision and Machine Learning from École Normale Supérieure Paris-Saclay.

Prior to joining QuantStack, Julien worked as a Research Software Engineer at Inria.

Julien's principal interests sit at the intersection of Applied Mathematics, Computer Science, and Software. Julien also co-maintains scikit-learn on his decreasing free-time.

Justine leads the data science team at HelloWork, a digital provider of employment, recruitment, and training solutions. She spent the last 10+ years enjoying machine learning, python and other data science fun stuff in various fields. Her current work includes a good deal of natural language processing.

Katharine Jarmul is a privacy activist and author of Practical Data Privacy (O'Reilly 2023). She has worked in privacy, security & ethics in machine learning & data for more than 10 years and rants about building things differently at probablyprivate.com.

Kevin is a Data Scientist at QuantCo, where he's been working with insurances on fraud detection, risk modelling and policy learning. In the past two years he's gotten into the field of Causal Inference. Prior to joining QuantCo, he majored in Computer Science at ETH in Zurich - focusing on Theoretical Computer Science and Machine Learning. He's passionate about Open Source and is the organizer of the PyData Zurich meetup.

I'm a data scientist in the innovation lab at Insee, the French statistics institute. I'm also very involved in teaching Python, mainly in engineering courses: for beginners (https://pythonds.linogaliana.fr/) or for data scientists wishing to discover cloud technologies (https://ensae-reproductibilite.github.io/website/).

Louis Lacombe, Data Scientist at Capgemini Invent, France.

Louis Lacombe, a graduate of the MSc program at the University of Bocconi, joined Quantmetry (now Capgemini Invent) in 2022. He began his journey in conformal predictions with the implementation of conformalized quantile regression in the MAPIE library.
Currently, he is one of the core developers of the library and focuses on enhancing its visibility by demonstrating diverse use cases and by integrating conformal predictions into clients' algorithms and advocating for a trusted AI approach.

ML Engineer @xtream

I am a freelance Machine Learning Engineer
I have applied data science and machine learning in various industries. I have grown to enjoy taking things from idea to production and I now have a strong grip on most of the satellite fields of data science (data engineering, devops/mlops, unit testing, containers, git and CI/CD, cloud, product development).
I am mostly interested in work that have a neutral if not positive impact on climate change and biodiversity. I spare some time off missions so I can dedicate it to open source project like Code Carbon

Maarten Breddels is an entrepreneur and ex-scientist mainly working with Python, C++, and Javascript in the Jupyter ecosystem. He is the creator of Solara, ipyvolume, and Vaex and Co-founder of Widgetti. His expertise includes fast numerical computation, API design, 3D visualization, and building data apps. He has a Bachelor's in ICT, a Master's, and Ph.D. in Astronomy, and he likes to solve real problems.

Pythonista and software engineer at Strasbourg Astronomical Data Centre.

Marco is a core dev of pandas and Polars and works at Quansight Labs as Senior Software Engineer. He also consults and trains clients professionally on Polars. He has also written the first Polars Plugins Tutorial and has taught Polars Plugins to clients.

He has a background in Mathematics and holds an MSc from the University of Oxford, and was one of the prize winners in the M6 Forecasting Competition (2nd place overall Q1).

Maria's professional goal is to improve the environment by understanding it first in
the language of mathematics and then applying the gained knowledge.
After graduating in applied mathematics, Maria began research on the two-phase turbulent flows.
Knowledge of mathematical modeling helped her better understand the small-scale physical effects
and allowed her to more accurately model two-phase turbulence while reducing computational costs.

After completing her PhD, Maria began to work as a data scientist.
She was responsible for all stages of data processing, from creating ETL pipelines, through modeling
to visualization of the results and leading 2-5 people projects.
Her inclination towards the implementation and design aspects gravitated her towards functional programming.
She integrated Haskell into parts of the data processing pipelines, finding its type system and
expressiveness more akin to mathematical language. Maria is also dedicated to maintaining neat,
reusable, and well-documented code.

Outside of her technical pursuits, Maria is passionate about promoting diversity in the IT industry
and inspiring girls and women to engage in programming. Balancing her career with being a mother of three,
she finds limited but cherished time for personal hobbies. When the opportunity arises,
Maria enjoys the thrill of motorcycle rides beyond the city limits.

Software rust/javascript developer working at the Strasbourg astronomical data center on the Aladin Lite web visualizer.

https://maxhalford.github.io/bio/

Merve is a machine learning advocate engineer at Hugging Face. She enjoys contributing to open-source and researching about multimodality, foundation vision models and how to make them more accessible through optimization.

Software Developer with a passion for package management systems and focused on developer experience. Previously worked on high-load online marketplace, fintech trading platform and monorepo management tool.

Nicolas is a Sr. ML Engineer at GitGuardian where he develops NLP-based technologies to detect vulnerabilities in code and provide remediation. He was previously Sr. Applied Scientist at Amazon Alexa where he developed the models that power Alexa's core understanding capabilities. He published multiple academic papers at top tier NLP conferences in the field of semantic parsing. Nicolas has hands-on experience with a variety of NLP models applied to client-facing applications.

Professor of Computer Science at the Laboratoire Interdisciplinaire des Sciences du Numériques of Université Paris-Saclay. Read more.

I am an Engineering Manager (for Data Science projects) at Sicara, where I worked on a wide range of projects mostly related to vector databases, computer vision, prediction with structured data and more recently LLMs.
I am currently leading the GenAI development in the company.
You can find all my talks and articles here: https://www.sicara.fr/en/noe-achache, e.g.
- https://www.sicara.fr/blog-technique/how-to-choose-your-vector-database-in-2023
- https://www.youtube.com/watch?v=aX_hdQEintc

Nour leads the Generative AI technical group at Modus Create. She has a PhD in Machine Learning. and has worked on Machine Learning, Data Science and Data Engineering problems in various domains, both inside and outside Academia.

Olivier is an Open Source Fellow at probabl and a core contributor to the scikit-learn machine learning library.

Patrick Hoefler is a member of the pandas core team and a Dask maintainer. He is currently working at Coiled where he focuses on Dask development and the integration of a logical query planning layer into Dask. He holds a Msc degree in Mathematics and works towards a Msc in Software engineering at the University of Oxford.

Pierre Raybaut is a long-term advocate of Python in a scientific context, renowned as the creator of Spyder, the Scientific Python IDE, and other pivotal projects like Python(x,y) and WinPython. These tools have been instrumental in making Python a leading language for scientific computing.

Pierre's academic journey began with an engineer's degree from the Institut d’Optique Graduate School, specializing in laser physics. He further advanced his expertise by earning a PhD in optics and photonics from Université Paris-Saclay, where he developed software for simulating regenerative amplification in ultra-short pulse lasers.

Professionally, Pierre has held diverse and impactful roles. He served as a research engineer at THALES Avionics, a principal software developer at CEA (the French Alternative Energies and Atomic Energy Commission), and managed the Laser MégaJoule timing and fiducial system project. Eventually, he became the Head of a Research Laboratory at CEA before transitioning to Codra, an industrial software company, where he currently holds the position of Chief Technology Officer (CTO).

Beyond his work on Spyder, Pierre is deeply involved in the open-source software community. He has created tools such as guidata, PlotPy, PlotPyStack and DataLab, and has contributed to numerous other projects.

I am a cloud service architect at Mercator Ocean international, developing a public core infrastructure for the European Digital Twin Ocean.

Rick Ratzel is a member of the RAPIDS team at NVIDIA, working on cuGraph - a library of GPU-accelerated graph algorithms. Rick joined NVIDIA in January 2019, bringing several years of experience as a technical lead for teams in industries that include test and measurement, electronic design automation, and scientific computing.

Sometimes a compiler engineer, sometimes a wood chopper, but also a retired wizard of the coast. Enjoy telling stories, be it old legends or modern bit yarns.

I'm a data / software engineer at Modus Create, working on projects in GenAI and biotech domains. I have a background in physics and computational structural biology.

Sophia Yang is the Head of Developer Relations at Mistral AI, where she leads developer education, developer ecosystem partnerships, and community engagement. She is passionate about the AI community and the open-source community, and she is committed to empower community growth and learning.

Stefanie is an open source developer at :probabl. and a contributor to scikit-learn.

Thibault Cordier is a Data and Research Scientist at Capgemini Invent, where he is a member of the Lab Invent team in France and serves as the technical leader of the MAPIE project.

Prior to joining the research team at Capgemini Invent, he earned his PhD in Computer Science in 2023 at Avignon University.

Up to now, his research has focused on distribution-free inference and conformal prediction, with applications in computer vision, natural language processing, and time series analysis.

Thorsten Beier is a Scientific Software Developer at QuantStack. He got his PhD at the University of Heidelberg (Germany) on Multicut Algorithms for Neurite Segmentation.

Tim is a Quantitative Developer at Cubist Systematic Strategies and an adjunct professor in the Computer Science Department at Columbia University.

Le Duc Trung is a Scientific Software Developer at QuantStack. He works on several projects within the Jupyter ecosystem, from the main projects like JupyterLab, Voilà, and ipywidgets to various JupyterLab extensions and widgets.

Senior Data Scientist @ Capgemini Invent

Getting onboard to lead the team behind MAPIE, an open-source library within the sklearn-contrib ecosystem, focused on conformal predictions.

After earning a MSc in Computer Science from École Centrale, I spent a few years in product management before returning to more technical roles.

Let’s connect!

Zhihan is a data scientist/engineer with a rich academic background in
pure mathematics. Having earned a PhD in Geometric Topology and Probabilities
from Telecom Paris, she defined random walks on simplicial complexes and
applied machine learning algorithms for in-depth analysis.

At Tweag (an Open Source Program Office of Modus create),
Zhihan brings mathematical rigor to the forefront of
data science and data engineering. She is actively engaged in developing
innovative data engineering solutions and crafting compelling data
visualizations, all while embracing the challenges of cloud deployment.