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PhD candidate in geometric statistics @Inria.
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Assessing your cultural and operational fit
Inria
Data Scientist
June 27, 2026 – Present
flag-trick
December 9, 2024 – December 16, 2025
Authors' implementation of the preprint "Nested subspace learning with flags".
View Projectprincipal-subspace-analysis
June 27, 2024 – Present
Authors' implementation of "The Curse of Isotropy: from Principal Components to Principal Subspaces" (Szwagier and Pennec, Statistical Science, 2026).
View ProjectMPSA
May 2, 2024 – November 7, 2025
Authors' implementation of the preprint "Parsimonious Gaussian mixture models with piecewise-constant eigenvalue profiles".
View Projectstratified-pca
September 21, 2023 – September 25, 2023
Authors' implementation of the preprint "Stratified Principal Component Analysis".
View Projectflag-manifold-distance
May 15, 2023 – August 21, 2023
Authors' implementation of the paper "Rethinking the Riemannian Logarithm on Flag Manifolds as an Orthogonal Alignment Problem".
View Projecttomszwagier.github.io
July 14, 2022 – August 29, 2023
Github Pages template for academic personal websites, forked from mmistakes/minimal-mistakes
View ProjectCultural Fit Analysis
The candidate's projects are highly academic and research-focused, primarily in advanced statistical learning and geometric data analysis. While this demonstrates deep technical expertise, the lack of diverse project types (e.g., industry applications, large-scale data processing, MLOps) might indicate a narrower scope of experience for a general Data Scientist role in a typical industry setting. The single current employment at a research institution further supports this specialized profile. This specialization might require a specific organizational culture that values deep theoretical research over broad application development.
Soft Skills & Operational Fit
Insufficient data to assess soft skills, logical reasoning, work attitude, stress handling, or team collaboration. The psychometric test score is 0, providing no insights.