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Data Governance and AI

Posted Feb 16, 2024 | Views 504
# Data governance
# AI
# Gjensidige
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Alexandra Diem
Head of Cloud Analytics & MLOps @ Gjensidige

Former academic turned data scientist with a passion for data mesh architectures.

🔬 Background in applied mathematics and statistics, adept at leveraging data-driven insights to solve complex problems. Experienced in diverse domains spanning the private and public sectors.

🧠 Made significant contributions to research in physiological modeling, successfully debunking a leading biomedical hypothesis on Alzheimer's disease during my PhD. Developed innovative approaches to quantify blood supply to the heart.

💡 Solution-oriented thinker with a track record of efficiently tackling challenging problems and adapting to novel scenarios.

⚙️ Expertise: Data Science | Mathematical Modeling | Statistical Analysis | Problem Solving

In my spare time, you'll find me exploring the great outdoors—whether it's pedaling through scenic landscapes on a bike or riding down the slopes on a pair of skis.

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Demetrios Brinkmann
Chief Happiness Engineer @ MLOps Community

At the moment Demetrios is immersing himself in Machine Learning by interviewing experts from around the world in the weekly MLOps.community meetups. Demetrios is constantly learning and engaging in new activities to get uncomfortable and learn from his mistakes. He tries to bring creativity into every aspect of his life, whether that be analyzing the best paths forward, overcoming obstacles, or building lego houses with his daughter.

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SUMMARY

This recent session featuring the incredibly talented Alexandra Diem delves into the challenges of generative AI in sensitive data environments, the emergence of specialized chatbots, and data governance. Balancing high-tech projects with those offering significant business value, using agile methods, is also discussed. Alexandra's journey from academia to being a consultant in Norway is truly inspiring. The discussion explores the function of enabling and R&D in tech roles, the shift towards self-serve solutions, and the integration of AI into existing workflows. Stimulating conversations about future-oriented technologies married with sound data science and industry practices make this session a must-listen for anyone interested in machine learning operations!

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