Matthias Darblade
Verified Expert in Engineering
Algorithms Developer
Buenos Aires, Argentina
Toptal member since October 21, 2019
Matthias is an actuary with over six years of experience in machine learning. He was the chief data scientist in a multinational company—leading AI projects in eight countries. The types of projects that Matthias are looking for would ideally involve deep learning, analytics, and data-related tasks.
Portfolio
Experience
Availability
Preferred Environment
Pandas, Jupyter, Python
The most amazing...
...application I've built was the one where I implemented reinforcement learning for cost optimization.
Work Experience
Quant
Family Office
- Backtested and implemented market-making strategies. Created a cross-chain execution engine.
- Worked on tokenomics and planning of IDO for several projects.
- Developed and maintained a protocol for semi-algorithmic stablecoins.
Lead Data Scientist
Chewse
- Worked remotely as the acting lead data scientist for a Series C startup based in San Francisco.
- Created the core business optimization model for supply matching. The model uses a similar architecture to Google's AlphaGo and was written in Python with C++ binding.
- Maintained high-code quality through code reviews, automated tests, and continuous integration.
- Composed several reports and insights to improve supply matching using graph theory, statistic inference, and machine learning.
Corporate Head of Data Science
Prosegur
- Led the churn-reduction program with an objective of a 20% reduction in churn across eight countries.
- Oversaw the development of the machine-learning algorithms and management of external resources to design and implement the final architecture.
- Created a machine-learning algorithm to improve the mobile application of the company. This algorithm understood client behavior to remind them of actions they might have forgotten to do.
- Supervised the hiring, building, and leading of a team of three data scientists. Led a team of five consultants based in Spain.
- Developed a financial analysis to justify capital investment into data-science projects.
Global Data Scientist
BNP Paribas Cardif
- Defined and developed a dynamic pricing library for automobile insurance in Chile.
- Performed R&D at the data laboratory of the head office in Paris (NLP, deep learning, and so son).
- Combined artificial intelligence and behavioral economics to automate claim payments.
- Built a tool to improve quarterly closing. The time for closing went from one month per quarter to four days per quarter.
- Improved a reserve calculation algorithm to not depend on human interactions for predictions.
- Automated the back-testing of several finance algorithms for the quick development of solutions.
Lecturer
Universidad de Buenos Aires
- Pitched and lectured a course about machine learning for actuary students in one of Latina America's most prestigious universities.
- Taught various concepts of data science and Python to students.
Actuary
Actuaris
- Consulted with various clients on actuarial science and portfolio analyses.
- Segmented a health insurance company portfolio to predict the financial impact of a new regulation and gave recommendations to clients as to what type of product to develop.
- Led the yearly update for a product of Addactis PM Export and coordinated and tested the development of the software with the engineering team.
- Gave talks about the use of machine learning to learn about client behavior.
Experience
Development of a Real-time Pricing Strategy
The model combined game theory, behavioral economics, and machine learning to bring profitability to the car insurance industry, which is known for having an extremely low return on investment.
Supply Matching Algorithm
Recomender System
Education
Master's Degree in Actuarial Science, Finance, and Risk Engineering
ISFA | Institute of Financial Science and Insurance - Lyon, France
Bachelor's Degree in Mathematics and Management
Université Claude Bernard Lyon 1 - Lyon, France
Skills
Libraries/APIs
PySpark, TensorFlow, Pandas, PyTorch, Keras, Scikit-learn
Tools
Microsoft Excel, Periscope Data, Jupyter
Languages
Python, Python 3, SAS, SQL, Go, C++, Excel VBA
Frameworks
Spark, Hadoop, Flask, Django, Cosmos SDK
Industry Expertise
Insurance, Healthcare, Retail & Wholesale
Platforms
Linux, Amazon Web Services (AWS)
Other
Artificial Intelligence (AI), Big Data, Natural Language Processing (NLP), Risk Models, Machine Learning, Data Science, Graph Theory, Schedule Optimization, Algorithms, Cosmos, Cryptocurrency, Generative Pre-trained Transformers (GPT), Neural Networks, Deep Learning
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