Skills
Machine Learning: deep learning models (including LLMs, Transformers, DNNs, CNNs, LSTMs/RNNs, Graph NNs), stochastic gradient descent methods, ELBO, Reinforcement Learning, (Multiple-Output) Gaussian Processes, kernel methods, orthogonal projection methods, Principal Components Analysis (PCA) and Probabilistic PCA,
variational autoencoder models
Time-Series: Time-Series Regressions, Functional Time-Series, Causal inference, VARMAX models, State-space models, Counting processes, MIDAS models, growth models, stochastic volatility, Autoregressive Distributed Lag (ARDL) models; simulation, estimation, calibration, toolbox and visualization design
Computational Finance and Econometrics: risk modelling, portfolio modelling, diversification analysis, factor models (CAPM, FFM models), stress testing, interest rate modelling and fixed-income, cryptocurrency modelling, optimal decision-making under uncertainty, long memory and persistence
Programming Languages: Python, MatLab, C/C++, SQL, Rust, Julia, Java
Generative AI: LLM pipelines, Retrieval-Augmented-Generation systems, LangChain, LlamaIndex, llama.cpp
Software, Toolboxes & Databases: Jax, PyTorch, HuggingFace AI libraries, Pyro, NumFOCUS suite and visualization libraries, MongoDB/SQLite, Mathworks MatLab (Digital Signal Processing Toolbox, Image Processing Toolbox, Numerical Analysis, Control Systems, Control Systems Design, Neural Networks), KALDI Speech
Recognition Toolkit
Collaboration Tools: Version Control Systems (git)
Remote processing and Cloud Services: accessing infrastructure and deploying scientific code at a large scale (SLURM), multiprocessing on CPU/GPU clusters and supercomputers (GENCI Jean Zay), Amazon Web Services set-ups, Containerization (Docker, Singularity), Jenkins (CI/CD)
About
Versatile machine learning engineer and researcher with 10+ years of experience developing advanced AI/ML systems across academia and industry (tech, fintech). Strong statistical modelling background with hands-on engineering skills in NLP, time-series modelling, statistical causal inference, and machine learning/AI. Skilled at deploying scalable ML pipelines, collaborating across disciplines, and rapidly adapting to new technologies and domains.
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