Julian Wergieluk-CEO & ML Engineer
Check rate
Experience
CEO & ML Engineer
LOLML GmbH
- 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
Machine Learning Engineer
DataRobot
- 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)
Quantitative Analyst
Allianz Global Investors (risklab)
- 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#)
Research Associate
University of Freiburg
- 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
Research Associate
Chemnitz University of Technology
- 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
Quantitative Analyst
Raiffeisen Bank International AG
Industry experience
See where this freelancer has spent most of their professional time.
Experienced in Banking and Finance, Education, Information Technology, Manufacturing, Energy, and Pharmaceutical.
Business area experience
See which departments and functions this freelancer has contributed to most.
Experienced in Finance, Research and Development, Information Technology, Investments and M&A, Operations, and Product Development.
Summary
A versatile engineer with in-depth mathematics, machine learning, and software development skills.
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
Languages
Education
Vienna University of Technology
Dipl.-Ing. degree in mathematics, focus on abstract algebra (group theory, homology theory), topology, symbolic computation and · Mathematics · Vienna, Austria
Certifications & licenses
Deep Reinforcement Learning, a Nanodegree
risklab (Allianz Global Investors)
Deep Learning, a 5-course Specialization
deeplearning.ai on Coursera
Statistics
Experience
Global experience
Expertise
Qualifications
Profile
Frequently asked questions
Have questions? Find more information here.
Julian speaks the following languages: Polish (Native), German (Advanced), English (Advanced), Japanese (Elementary).
Julian has at least 19 years of experience. During this time, Julian has worked in at least 4 different roles and for 6 different companies. The average length of individual experience is 3 years and 1 month. Note that Julian may not have shared all experience and actually has more experience.
Based on recent experience, Julian would be well-suited for roles such as: CEO & ML Engineer, Machine Learning Engineer, Quantitative Analyst.
Julian's most recent position is CEO & ML Engineer at LOLML GmbH.
In recent years, Julian has worked for LOLML GmbH and DataRobot.
Julian is most experienced in industries like Banking and Finance, Education, and Information Technology. Julian also has some experience in Manufacturing, Energy, and Pharmaceutical.
Julian is most experienced in business areas like Research and Development, Finance, and Investments and M&A. Julian also has some experience in Information Technology, Operations, and Product Development.
Julian has recently worked in industries like Banking and Finance, Information Technology, and Manufacturing.
Julian has recently worked in business areas like Information Technology, Finance, and Operations.
Julian holds a Master in Mathematics from Vienna University of Technology.
Julian has 2 certificates. These include: Deep Reinforcement Learning, a Nanodegree, Deep Learning and a 5-course Specialization.
The availability of Julian needs to be confirmed.
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