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Math + Bayes = life choices. Exploring Bayesian ML, writing unnecessarily fast C++, and living inside NixOS configs. Side quest: maintaining a 2-node cluster
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Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Inria
Data Scientist
June 27, 2026 – Present
BNPClust
July 22, 2025 – Present
Flexible Bayesian clustering framework with MCMC inference. Supports multiple nonparametric priors (DP, NGGP), distance-based models, and state-of-the-art samplers including Split-Merge algorithms. Built in C++ for efficient computations.
View ProjectOnline-Learning-Application-project
April 22, 2025 – September 7, 2025
This repo contains the code developed for the project part of the course Online Learning Application at Politecnico of Milan
View Projectfmap
November 4, 2024 – April 11, 2025
Artificial Neural Networks and Deep Learning code repository of "fmap" group
View ProjectSplit_and_merge_Gibbs_sampling
July 15, 2024 – December 3, 2025
This repository implements a Gibbs sampling algorithm for Bayesian inference of Dirichlet process mixture models with Hamming distributed kernels. The approach provides model-based clustering for categorical data that lacks natural ordering. Our implementation incorporates split-and-merge Markov chain Monte Carlo techniques to efficiently navigate
View ProjectElectricity-spot-market-prediction
March 20, 2024 – July 16, 2024
This project analyzes electricity spot market demand and offer curves to predict the equilibrium price.
View ProjectPACS-challenges
March 10, 2024 – July 1, 2024
This repo contain the code used for solve the challenges of the course PACS (Advanced Programming for Scientific Computing))
View Projectknn_cuda
November 12, 2023 – January 2, 2024
KNN written in CUDA without any external library like CUBLAS or anything else
View ProjectCultural Fit Analysis
The candidate's projects are predominantly personal and research-oriented, showcasing deep technical interests in statistical modeling, machine learning, and high-performance computing. The current role as 'Data Scientist' at Inria aligns well with the target role. However, the lack of diverse project types (e.g., team projects, open-source contributions, industry-specific applications) and limited experience details make it difficult to fully assess cultural fit beyond a strong technical alignment. The focus on C++ and R for statistical computing is a good fit for research-heavy data science roles.
Soft Skills & Operational Fit
Insufficient data to assess soft skills and operational fit. The candidate's project descriptions indicate a strong technical focus and ability to work on complex, self-directed projects. However, there is no information regarding collaboration, communication style, or problem-solving approach in a team setting.