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Ph.D. candidate at BMW Group, Pasqal, CERFACS and FAU
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
ENS Paris Saclay
Applied Mathematics & Data Science
January 1, 2016 – January 1, 2017
École Polytechnique
Master’s Degree, Applied Mathematics and Computer Science
January 1, 2013 – January 1, 2017
CERFACS
Research Engineer in Quantum AI for CFD
November 1, 2025 – April 1, 2026
Toulouse · On-site
BMW Group
Quantum Computing & Machine Learning Research Engineer
May 1, 2022 – Present
Munich, Bavaria, Germany
FAU Erlangen-Nürnberg
Ph.D. Candidate
May 1, 2022 – Present
Munich, Bavaria, Germany
Sinequa
Machine Learning Engineer
November 1, 2018 – March 1, 2021
Paris, Île-de-France, France
Amazon Web Services
AWS Deep Learning, Applied Scientist Intern
April 1, 2017 – October 1, 2017
San Francisco Bay Area
Université de Montréal
Research Intern at University of Montréal.
April 1, 2016 – August 1, 2016
Région de Montréal, Canada
Crédit Agricole CIB
Business Analyst-Developer
June 1, 2015 – September 1, 2015
Singapore
France Ministry of Education
Leadership Training
October 1, 2013 – March 1, 2014
Région de Toulouse, France
French Armed Forces
Basic training
September 1, 2013 – September 1, 2013
Courtine, France.
Market impact in high-frequency trading.
September 1, 2015 – Present
- Market Order flow and Price jumps modelling with multidimensional Hawkes processes - Non-parametric calibration of the model with high frequency data - Estimation of the Hidden Orders Impact
Minimum Bandwidth Problem.
September 1, 2015 – Present
- Graph theory, graph labeling, - Optimisation problem.
Project in robotics.
April 1, 2015 – June 1, 2015
This project aims to develop an algorithm in ROS to enable a drone to follow a wall or go around a building autonomously. -ROS -Python algorithms -Scikit-learn -OpenCV
Rubik's Cube Solving.
November 1, 2014 – January 1, 2015
- Design algorithm to solve a Rubik's Cube using pattern DataBase, - Java Swing GUI. Reference : https://www.cs.princeton.edu/courses/archive/fall06/cos402/papers/korfrubik.pdf
Preparing for the Google Cloud Professional Cloud Architect Exam
Coursera
June 24, 2026 – Present
Machine Learning
Coursera Course Certificates
June 24, 2026 – Present
Neural Networks and Deep Learning
Coursera
June 24, 2026 – Present
IBM Quantum Challenge - Fall 2021 - Advanced
IBM
June 24, 2026 – Present
Google Cloud Fundamentals: Core Infrastructure
Coursera
June 24, 2026 – Present
Essential Google Cloud Infrastructure: Foundation
Coursera
June 24, 2026 – Present
Google Cloud Big Data and Machine Learning Fundamentals
Coursera
June 24, 2026 – Present
How Google does Machine Learning
Coursera
June 24, 2026 – Present
Essential Google Cloud Infrastructure: Core Services
Coursera
June 24, 2026 – Present
Elastic Google Cloud Infrastructure: Scaling and Automation
Coursera
June 24, 2026 – Present
Launching into Machine Learning
Coursera
June 24, 2026 – Present
Architecting with Google Kubernetes Engine: Foundations
Coursera
June 24, 2026 – Present
Reliable Google Cloud Infrastructure: Design and Process
Coursera
June 24, 2026 – Present
PennyLane Code Camp Explorer
Xanadu
June 24, 2026 – Present
Preparing for Google Cloud Certification: Cloud Architect Specialization
Coursera
June 24, 2026 – Present
Google Cloud Essentials
Qwiklabs
June 24, 2026 – Present
IBM Certified Associate Developer - Quantum Computation using Qiskit v0.2X
IBM
June 24, 2026 – Present
Perform Foundational Infrastructure Tasks in Google Cloud
Qwiklabs
June 24, 2026 – Present
Deploy to Kubernetes in Google Cloud
Qwiklabs
June 24, 2026 – Present
Introduction to TensorFlow
Coursera
June 24, 2026 – Present
IBM Quantum Spring Challenge 2022 Achievement
IBM
June 24, 2026 – Present
Fundamentals of Accelerated Computing with CUDA Python
NVIDIA
June 24, 2026 – Present
Qiskit Global Summer School 2022 - Quantum Excellence
IBM
June 24, 2026 – Present
IBM Quantum Challenge Fall 2022 Achievement - Advanced
IBM
June 24, 2026 – Present
PennyLane Code Camp Adventurer
Xanadu
June 24, 2026 – Present
Cultural Fit Analysis
The candidate's background is heavily skewed towards research and advanced scientific computing, particularly in Quantum AI and Deep Learning. While this demonstrates a high level of technical capability, the target role of 'Data Analyst' might not fully leverage their deep expertise in these specialized areas. The project diversity, ranging from Rubik's Cube algorithms to high-frequency trading and robotics, indicates a broad intellectual curiosity and adaptability. The academic rigor from École Polytechnique and ENS Paris Saclay, combined with experience at companies like BMW and AWS, suggests a fit for high-performance, innovation-driven environments. However, the direct alignment with typical data analyst responsibilities (e.g., dashboarding, routine reporting, business intelligence) is not explicitly strong, suggesting a potential overqualification or a need to adapt to a more business-focused analytical role.
Soft Skills & Operational Fit
The candidate's project descriptions indicate a strong problem-solving aptitude and an interest in complex, research-oriented challenges. The diverse range of projects and academic pursuits suggests intellectual curiosity and a proactive approach to learning. However, without direct assessment data, specific soft skills like teamwork, leadership, or stress handling cannot be definitively evaluated. The experience as a Mathematics and Physics instructor suggests communication and teaching abilities.