Home 5 Projects 5 Machine Learning Models @ BNP Paribas, 2020-2022

Machine Learning Models @BNP Paribas, 2022-2024

Deploying and bringing out Machine Learning Engineers and Data Scientists everyday work artifacts to end-users.

Tech stack:

Openshift

Openshift

Helm

Helm

Sonatype

Sonatype

Docker

Docker

Kafka

Kafka

Spark

Spark

Go

Crisp-ML

Crisp-ML

Flask

Flask

Python

Python

Click to Expand section and show all tech used for this project

Story

After being hired by a Bank within a transformative data science department: our aim became clear – we were to fulfill one of the broad IT strategy goals for implementation of custom-built machine learning models.

 

Solution

The challenge turned out to be of a large scope, and it required not only implementing thought-out best coding practices, but also conducting educational activities, with occasional hints of knowledge-sharing.

 

Deployment in models creation process

 

Way of working – CrispML

 

Lesson Learned

I have learned that working within such a large Organization requires one to be a flexible person, that is ready for adapting to changing conditions every day. On the one hand, it is required from an employee on an everyday basis, but also such an approach needs to be implemented and come out of hand-crafted code solutions.

        Statistics

        • Not available – the whole project has been a private property of BNP Paribas Bank Polska S.A.