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Jānis Ducens

Jānis Ducens

Technical Support Engineer
Riga, Rīga
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Sociālā vietne


Par Jānis Ducens:

Highly analytical professional with over 9 years of experience successfully fulfilling incident and service requests within Linux/Unix systems within SLA requirements. Well-versed in customer service with excellent communication and documentation skills. Demonstrated expertise in mentoring junior members of 1st tier support team. Proficient in optimising customer implementations through comprehensive feature and update testing, streamlined deployment, debugging, and automated updating. Possess an in-depth understanding of Python's NLP process encompassing tokenization, vectorization, artificial neural network architectures, and PySpark's RDD. Expertise in efficient data extraction processing and automation scripting using bash, regex, and awk. Adept at translating client requirements into functional deliverables by extensively leveraging programming languages, such as Python and Java, and WEB programming with LAMP, comprising Apache, MySQL, PHP, JavaScript, and CSS.

Pieredze

  • Extensive experience in providing exceptional customer support, adhering to support guidelines and SLAs, and effectively resolving product-related issues through troubleshooting and escalation, ensuring customer satisfaction.
  • Strong background in Linux administration with hands-on experience of over 9 years, demonstrating proficiency in managing and maintaining Linux systems.
  • Solid understanding of SQL and ability to write basic queries, coupled with a comprehensive grasp of orchestration and Kubernetes, enabling effective collaboration with engineering teams for product enhancement.
  • Skilled and experienced in applying state-of-the-art Machine Learning techniques, including Natural Language Processing (NLP) and Text Vectorization, to effectively classify and secure unstructured data in real-time, enabling the discovery, categorization, and classification of documents and emails across on-premises and cloud environments.

Izglītība

I have experience doing research on the performance of multiple sequential and non-sequential Python algorithms for categorizing text.

  • During my Master's thesis, I experimentally discovered the best-performing combinations of vector formats, ANN architectures, and optimizers backed with analysis and conclusions of their appropriate metrics.
  • During my Master's studies, I developed a conceptual solution for an artificial pancreas device using elements of artificial intelligence for patients with 1st type diabetes.
  • In my Bachelor's thesis, I explored the impact of RPA (Robotic Process Automation) on business processes, focusing on the improvement of performance metrics.

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