Matthias Darblade, Developer in Buenos Aires, Argentina
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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.


Family Office
Go, Cosmos SDK, C++, Cosmos, Cryptocurrency
Algorithms, TensorFlow, Pandas, Scikit-learn, SQL, Python 3...
TensorFlow, Pandas, SQL, Python 3, Artificial Intelligence (AI)...




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


2019 - 2022
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.
Technologies: Go, Cosmos SDK, C++, Cosmos, Cryptocurrency

Lead Data Scientist

2018 - 2020
  • 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.
Technologies: Algorithms, TensorFlow, Pandas, Scikit-learn, SQL, Python 3, Artificial Intelligence (AI), Machine Learning, Python, Graph Theory, Data Science

Corporate Head of Data Science

2017 - 2019
  • 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.
Technologies: TensorFlow, Pandas, SQL, Python 3, Artificial Intelligence (AI), Machine Learning, Python, PySpark, Data Science, Excel VBA

Global Data Scientist

2014 - 2017
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.
Technologies: Pandas, SQL, Python 3, Machine Learning, SAS, Python, Insurance, Risk Models, PySpark, Data Science, Big Data, Excel VBA


2015 - 2015
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.
Technologies: Pandas, Python 3, Machine Learning, Python, Insurance, Risk Models, Data Science, Excel VBA


2013 - 2014
  • 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.
Technologies: Pandas, SAS, Microsoft Excel, Python, Insurance, Risk Models, Healthcare, Data Science, Excel VBA

Development of a Real-time Pricing Strategy

I developed a web scraper for an online insurance business in Chile and created a model to react to changes in competitors' prices for each segment.

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

I built out a supply matching algorithm for a startup using Python and C++ bindings. Using Monte Carlo Tree Search combined with a fast and slow neural network evaluator, the system determined the best possible move to improve overall COGS and reduce errors.

Recomender System

I created a recommender system for an Indian online video sharing platform. The system worked making recommendations at the end of each video with an API response time of 45 ms and was able to recommend based on context instead of pure similarity of content.
2012 - 2014

Master's Degree in Actuarial Science, Finance, and Risk Engineering

ISFA | Institute of Financial Science and Insurance - Lyon, France

2009 - 2012

Bachelor's Degree in Mathematics and Management

Université Claude Bernard Lyon 1 - Lyon, France


PySpark, TensorFlow, Pandas, PyTorch, Keras, Scikit-learn


Microsoft Excel, Periscope Data, Jupyter


Spark, Hadoop, Flask, Django, Cosmos SDK


Python, Python 3, SAS, SQL, Go, C++, Excel VBA


Data Science

Industry Expertise

Insurance, Healthcare, Retail & Wholesale


Linux, Amazon Web Services (AWS)


Artificial Intelligence (AI), Big Data, Natural Language Processing (NLP), Risk Models, Machine Learning, Graph Theory, Schedule Optimization, Algorithms, Cosmos, Cryptocurrency, Generative Pre-trained Transformers (GPT), Neural Networks, Deep Learning

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