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Irene Burresi
Data Scientist @ Value Partners | Specialising in AIOps and Cloud Computing
About Me
๐ ๐๐ฎ๐๐ฎ ๐ฆ๐ฐ๐ถ๐ฒ๐ป๐๐ถ๐๐ | ๐๐๐ฝ๐ถ๐ฟ๐ถ๐ป๐ด ๐๐/๐๐๐ข๐ฝ๐ ๐๐ป๐ด๐ถ๐ป๐ฒ๐ฒ๐ฟ I am Data Scientist. With a strong technical background, I am currently specializing in AIOps. ๐ฉโ๐ป ๐ง๐ฒ๐ฐ๐ต๐ป๐ถ๐ฐ๐ฎ๐น ๐ฆ๐๐ฎ๐ฐ๐ธ ๐๐ฎ๐๐ฎ ๐ฆ๐ฐ๐ถ๐ฒ๐ป๐ฐ๐ฒ: I have worked on various time series analyses and classification tasks. My main focus is on NLP and advanced use of Large Language Models (LLMs) with RAG and fine-tuning techniques. ๐ฃ๐ฟ๐ผ๐ด๐ฟ๐ฎ๐บ๐บ๐ถ๐ป๐ด ๐๐ฎ๐ป๐ด๐๐ฎ๐ด๐ฒ๐: Following a bottom-up approach, I laid a solid foundation by studying low-level languages (C) and then moved on to Java, Typescript, and Python. ๐๐ฒ๐๐ฒ๐น๐ผ๐ฝ๐บ๐ฒ๐ป๐ ๐ ๐ฒ๐๐ต๐ผ๐ฑ๐ผ๐น๐ผ๐ด๐ถ๐ฒ๐: I am a strong advocate of Test-Driven Development (TDD) and the application of SOLID and DRY principles. I also enjoy studying and applying design patterns wherever possible. ๐๐น๐ผ๐๐ฑ ๐ฃ๐น๐ฎ๐๐ณ๐ผ๐ฟ๐บ๐: I have experience with both AWS (especially for developing serverless microservices using Lambda, SQS queues, and API Gateway) and Azure (mainly OpenAI and Document Intelligence). ๐ ๐๐๐ฟ๐ฟ๐ฒ๐ป๐๐น๐ ๐๐ฒ๐ฎ๐ฟ๐ป๐ถ๐ป๐ด: ๐๐: AI is such a vast field that I can never fully explore it. Currently, I am focusing on various papers that illustrate the progress made in recent months with LLMs. ๐๐๐ข๐ฝ๐: This is the area of AI that I am most passionate about and where I feel I am most suited. I am acquiring specific certifications and strengthening my skills in Infrastructure as Code (IaC) and Continuous Integration/Continuous Deployment (CI/CD). ๐ก ๐ฃ๐ฟ๐ผ๐ณ๐ฒ๐๐๐ถ๐ผ๐ป๐ฎ๐น ๐ฃ๐ต๐ถ๐น๐ผ๐๐ผ๐ฝ๐ต๐: I firmly believe in the importance of an agile and "production-first" approach, even for AI projects. By applying agile methodologies, I promote the rapid development and release of functional MVPs to accelerate stakeholder feedback, clarify misunderstandings that often lead AI projects to fail prematurely, and refine products through continuous iterations. My mission focuses on bridging the gap between the development of AI models and their operational implementation, emphasizing feedback loops and retraining.
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Self Starter
Earned on Aug 20, 2024