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Applied Machine Learning
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Ecole normale supérieure
Doctor of Philosophy (Ph.D.), Theroretical Physics
N/A – Present
Weizmann Institute of Science
Post-Doc, Theoretical Physics
N/A – Present
California State University, Los Angeles
Master of Science - MS, Mathematics / Physics
N/A – Present
Oracle
Architect
January 1, 2025 – Present
KINETIX ai
Scientific Advisor
January 1, 2022 – January 1, 2024
Microsoft
Principal ML Scientist Lead
January 1, 2019 – January 1, 2025
SAP
Senior Data Scientist
January 1, 2016 – January 1, 2019
myThings
Data Scientist & Engineer
January 1, 2015 – January 1, 2016
Tempdrop
Scientific Advisor
January 1, 2014 – January 1, 2017
Tingz.me
Algorithm Developer
January 1, 2014 – January 1, 2015
Toldot Genetics Ltd
Data Scientist
January 1, 2014 – January 1, 2015
Scientra
Quantitative Analyst
January 1, 2013 – January 1, 2014
République française
Research Scientist
January 1, 2010 – January 1, 2012
Palais de la découverte
Lecturer
January 1, 2005 – January 1, 2008
Deep learning for pedestrians: backpropagation in Transformers
January 1, 2025 – January 1, 2025
Follow-up to our previous vectorized derivation of backpropagation: This time with a focus on Transformers Accompanying paper: https://arxiv.org/abs/2512.23329
Public key encryption for pedestrians: RSA + OAEP padding with a real SSH key
January 1, 2020 – January 1, 2020
https://github.com/Ranlot/public-key-encryption Deep dive into the mathematics of RSA algorithm, its homomorphic properties and the OAEP randomized padding. With concrete examples not commonly shown elsewhere. Accompanying paper: https://hal.science/hal-05359402
Real numbers, data science and chaos: How to fit any dataset with a single parameter
January 1, 2019 – January 1, 2019
We show how any dataset of any modality (time-series, images, sound...) can be approximated by a well-behaved (continuous, differentiable...) scalar function with a single real-valued parameter. (More than 600 stars on GitHub) Accompanying paper: https://arxiv.org/abs/1904.12320
Deep learning for pedestrians: backpropagation in CNNs
January 1, 2018 – January 1, 2018
Pedagogical introduction to the main concepts underpinning backpropagation with an emphasis on Convolutional Neural Networks. Novel formulation using vectorized algebra. Accompanying paper: https://arxiv.org/abs/1811.11987
AB tests: exposing the slow convergence of power statistics
January 1, 2017 – January 1, 2017
In-depth investigation of finite size effects and slow convergence of power statistics in the context of AB tests.
On the other side of the sea
January 1, 2017 – January 1, 2017
Imagine you're on your favorite beach staring straight out into the sea. If you followed this line of sight, where would you make first landfall and which countries would you cross until you come back home?
Spiral Net
January 1, 2017 – January 1, 2017
Looking at the manifold hypothesis in deep learning. Creating a simple spiral dataset allows me to reveal how neural networks follow an optimal packing strategy during their training.
Spark streaming: real-time visualization
January 1, 2016 – January 1, 2016
Simple demonstration of how to build a complex real time machine learning visualization tool
Number Theory and Cryptography
Coursera
June 24, 2026 – Present
Sequence Models (deeplearning.ai)
Coursera
June 24, 2026 – Present
Cultural Fit Analysis
The candidate's background is heavily skewed towards research, theoretical physics, and advanced machine learning/data science, with a strong emphasis on publishing and deep dives into complex algorithms. While this demonstrates exceptional intellectual rigor, the target role of 'Data Analyst' might be a mismatch for their senior-level, research-heavy profile. Their project diversity is high in terms of scientific topics, but less so in terms of typical data analyst tools or business-oriented reporting/dashboarding. The breadth of skills is exceptional in advanced analytics and ML, but specific data analyst tools (e.g., SQL, Tableau, Power BI) are not explicitly mentioned in the provided data. This profile might be overqualified or misaligned for a standard Data Analyst role, potentially leading to a lack of engagement with day-to-day analytical tasks.
Soft Skills & Operational Fit
The candidate's extensive experience in scientific advisory and leadership roles suggests strong problem-solving, critical thinking, and communication skills. The numerous personal projects and publications indicate a high degree of intellectual curiosity, self-motivation, and a drive for deep understanding. The diverse industry experience implies adaptability and the ability to work in varied operational contexts. However, without specific psychometric or English test scores, a direct assessment of soft skills like teamwork, stress handling, or professional language usage is limited.