As a contractor, I have contributed thoroughly to two major customers worldwide in different industries helping them to achieve success.

With HERE Technologies:
The customer had an ambitious project for Machine Learning as a Service platform but the path to reach there wasn't clear enough. I was the technical lead the team, and it was my responsibility plan and implement through a series of several PoCs in which we tested and validated several tools, techniques, and approaches that slowly started to clear the path to the final goal.

With my help and the rest of the team, the customer was able to clarify the roadmap and start pushing into production different versions of the product that helped their customers, data scientists, and software engineers, to succeed in terms of data and location services needs.

The stack and practices I used were Apache Spark, Apache Zeppelin, Jupyter, Scikit-Learn, Java, Scala, Python, Docker, Kubernetes, Terraform, Ansible, AWS, EMR, MongoDB, PostgreSQL with GIS support among others.

With Kinesso (IPG Mediabrands):
As a Data Scientist, I am responsible for understanding digital marketing and the company's business model along with the current Advanced TV implementation and find better options to implement it in both engineering and data exploitation perspectives and planning migrations for the parts worth of it. This will allow increasing the system throughput and data reliability as the company expects exponential adoption.

The stack I use is Jupyter, Python, Dask, AWS, SQS, RedShift, CPLEX

I was part of the maintenance/development team for Sonic ESB/MQ, now CX Messenger product, a JMS and ESB suite to build large and distributed SOA applications which, by this time, it was being used by major companies worldwide.

I significantly contributed to the core codebase of the product, solving very complex issues within the system reported directly by the product customers in production. Some of these issues were of maximum priority and causing money losses.

As a remote contractor, it was very challenging to solve complex issues without much help from peers, whether because they were in different time zones, they also had their own issues, or issues were latent bugs completely unknown for the rest of the engineers.

Aside from solving issues, I contributed to the automation of operational tasks that boosted up the developer's productivity, particularly with containerization and environment setup.

The stack and practices I used was Java, JMS, Databases, Docker, CI/CD, TDD, Bash & Python scripting, distributed systems, web services, and agile practices.