Irene Burresi

🚀 𝗗𝗮𝘁𝗮 𝗦𝗰𝗶𝗲𝗻𝘁𝗶𝘀𝘁 | 𝗔𝘀𝗽𝗶𝗿𝗶𝗻𝗴 𝗔𝗜/𝗔𝗜𝗢𝗽𝘀 𝗘𝗻𝗴𝗶𝗻𝗲𝗲𝗿

I am Data Scientist. With a strong technical background, I am currently specializing in AIOps.

👩‍💻 𝗧𝗲𝗰𝗵𝗻𝗶𝗰𝗮𝗹 𝗦𝘁𝗮𝗰𝗸

• 𝗗𝗮𝘁𝗮 𝗦𝗰𝗶𝗲𝗻𝗰𝗲: 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.
• 𝗣𝗿𝗼𝗴𝗿𝗮𝗺𝗺𝗶𝗻𝗴 𝗟𝗮𝗻𝗴𝘂𝗮𝗴𝗲𝘀: 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.
• 𝗗𝗲𝘃𝗲𝗹𝗼𝗽𝗺𝗲𝗻𝘁 𝗠𝗲𝘁𝗵𝗼𝗱𝗼𝗹𝗼𝗴𝗶𝗲𝘀: 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.
• 𝗖𝗹𝗼𝘂𝗱 𝗣𝗹𝗮𝘁𝗳𝗼𝗿𝗺𝘀: 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).

🔍 𝗖𝘂𝗿𝗿𝗲𝗻𝘁𝗹𝘆 𝗟𝗲𝗮𝗿𝗻𝗶𝗻𝗴:

• 𝗔𝗜: 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.
• 𝗔𝗜𝗢𝗽𝘀: 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).

💡 𝗣𝗿𝗼𝗳𝗲𝘀𝘀𝗶𝗼𝗻𝗮𝗹 𝗣𝗵𝗶𝗹𝗼𝘀𝗼𝗽𝗵𝘆:

• 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.