In my job as a Solution Engineer, I do three main things:Making Solutions Happen: I take ideas and turn them into real solutions for each customer at Zelros. From figuring out what they need to setting it up, it's about making things work for them.Helping People Use Solutions: I enjoy getting people excited about using our solutions. It's not just about business - it's about keeping customers happy and engaged by working together.Taking Care of Partnerships: I go beyond Zelros and make sure our partners have everything they need to use our solutions well for their clients. It's all about building strong relationships.🔍 Tech Side of Things: Alongside all this, I'm into the technical stuff. I handle SQL, work with different tools for monitoring, and write code in Python. When there are issues, I dig in and figure out what's going wrong to make our solutions better.

Full-stack Software development Engineer in Test Automation (external customer - Insurance Company):-Developing tools to be used by test automation teams (Java, Selenium, ORM, Typescript).-Design, implement and maintain the needed infrastructure (Bamboo, Jenkins, Nexus, Bitbucket, Docker, DevOps).-Creating reusable scripts/tools upon demand.-Personalized solutions for Business critical related testing, by interacting with all needed systems to automate some testing processes

Full-stack Software development Engineer in Test Automation (external customer - Insurance Company):-Developing tools to be used by test automation teams (Java, Selenium, ORM, Typescript).-Design, implement and maintain the needed infrastructure (Bamboo, Jenkins, Nexus, Bitbucket, Docker, DevOps).-Creating reusable scripts/tools upon demand.Full-Stack Software development:-development of a tool for HR (Javascript, nodejs).-development of Chrome extension (JS, nodejs)

-First Software developer professional experience-First software testing experienceData Science:-development of multiple Recommendations systems (Content-based, Collaborative Filtering), but also AI-Based RS (Python).-End to end Recommendations systems using NLP (numpy, pandas, nltk..) and Neural networks (Keras) to learn the right embeddings.-Developed the interface (Flask) for the users, to interact with the Recommendations systems, fine-tune the AI-Based RS with this data.-Evaluate the best RS according to the user's data we have, and let the backend decide which RS will be used for the Recommendation using a gateway.-Deploy using docker