Julian Wergieluk - CEO & ML Engineer

Germany

Experience

Jan 2023 - Present

3 years 1 month

Germany

Consulting: Monte-Carlo scenario analysis of an exotic swaps portfolio (C++, bash, gnuplot)
Project selection: Industrial Process Optimization, EDI-Automation, LLM Explainability, Portfolio Optimization, Time-Series

Nov 2019 - Dec 2022

3 years 2 months

Germany

Hybrid

Developed an internal VaR model for market risk
Teams:
Market scenario generator: hybrid Monte Carlo approach employing a 500-dimensional discretization of the Heath-Jarrow-Morton SPDE (C++ with STL, boost, blitz++, GSL)
Model Management and Monitoring (MLOps): online learning models for drift detection and feature distribution monitoring
Probabilistic credit market model: statistical analysis and calibration of a default probability term structure model for CDS spreads
ContagionNET: probabilistic individual infection risk model, working directly with the CEO
Covid Machine: vaccine trial optimization (Moderna), compartmental epidemic modeling
Trusted AI: implementation of a prediction intervals model for regression problems (conformal inference)

Sep 2015 - Oct 2019

4 years 2 months

Munich, Germany

Designed, implemented, and managed a portfolio optimization framework consisting of:
A C# backend employing various LP and QP optimizers from the NAG library
Middleware exposing a WebAPI and utilizing RabbitMQ
An async C# VSTO Excel frontend
Automated risk reporting and data validation processes (Python, Jupyter, bash, Cygwin)
Tested and validated a derivatives pricing framework covering inflation-indexed swaps (MATLAB, Python, C#)

Apr 2015 - Dec 2018

3 years 9 months

Python ML stack: numpy, pandas, matplotlib, PyTorch, scikit-learn, scipy, streamlit
Models: Deep Learning, NLP, Large Language Models, Time-series, Computer Vision, Reinforcement Learning
Research topics: financial mathematics, statistics, stochastic analysis, energy markets
Linux: standard UNIX tools (bash, vim, git, etc.); Arch Linux + i3
Teaching: mathematics for engineers, mathematical statistics, and stochastic analysis (8 courses)
Others: PyCharm, LaTeX
Published a problem book in probability and statistics

Feb 2011 - Mar 2015

4 years 2 months

Python ML stack: numpy, pandas, matplotlib, PyTorch, scikit-learn, scipy, streamlit
Models: Deep Learning, NLP, Large Language Models, Time-series, Computer Vision, Reinforcement Learning
Research topics: financial mathematics, statistics, stochastic analysis, energy markets
Linux: standard UNIX tools (bash, vim, git, etc.); Arch Linux + i3
Teaching: mathematics for engineers, mathematical statistics, and stochastic analysis (8 courses)
Others: PyCharm, LaTeX
Published a problem book in probability and statistics

Jan 2008 - Jan 2011

3 years 1 month

Vienna, Austria

A versatile engineer with in-depth mathematics, machine learning, and software development skills.

Python Ml Stack: Numpy, Pandas, Matplotlib, Pytorch, Scikit-learn, Scipy, Streamlit
Models: Deep Learning, Nlp, Large Language Models, Time-series, Computer Vision, Reinforcement Learning
Linux: Standard Unix Tools (Bash, Vim, Git, Etc.); Arch Linux+i3
Others: Pycharm, Latex