📍 Based in Denmark
🏢 Senior Data Scientist at Novo Nordisk
🎓 Biophysics PhD
🦀 Rust and Python Connoisseur 🐍
📧 Contact me | 🌐 Connect with me | 📂 Read me thoughts | 📊 Check out my work
As a Senior Data Scientist, I thrive at the intersection of cutting-edge machine learning, artificial intelligence, and statistics. Whether it's solving complex business problems or developing agentic frameworks for language models, my focus is on transforming data into actionable insights.
With a background in biophysics and data science, I've led a diverse range of projects, from automating processes with AI to optimizing supply chain operations. Currently, I’m applying these skills at NTT Data, where I also mentor the next generation of data scientists.
My main focus is on building and deploying machine learning and AI solutions that deliver tangible business impact. From creating predictive models that drive smarter decision-making to deploying AI systems into production, I cover the entire lifecycle of AI development to ensure real-world success.
Key Applications:
- Predictive modeling for business insights
- Deep learning frameworks for computer vision and NLP tasks
- End-to-end AI pipelines, from data processing to model deployment
I utilize Bayesian statistics to develop models that are more interpretable and better suited for decision-making under uncertainty. These methods allow for a more robust approach when dealing with incomplete data or when integrating prior knowledge into machine learning models.
Key Applications:
- Probabilistic models for uncertain environments
- Bayesian inference to improve predictions and decision-making
I’m also exploring the development of agent-based frameworks for large language models (LLMs). These frameworks extend the capabilities of LLMs, allowing them to autonomously handle workflows such as customer service automation or decision support.
Key Applications:
- Autonomous agents for process automation
- LLM-based conversational agents for task execution
- Azure Data Scientist Associate (2024)
- Azure AI Engineer Associate (2024)
- SnowPro Data Scientist (2023)
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UrbanAI: A simulation that models a city's traffic system using multi-agent technology. Agents handle traffic signals, emergency vehicles, public transportation, and pedestrian crossings to optimize urban traffic flow. Built using Python.
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Cassia: A Docking Window Forecast API built using weather and tide data to inform ships when they can dock at any harbor. Developed using Python.
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RusticLearning: A modular Rust machine learning pipeline using linfa. Includes models like Logistic Regression, KNN, and Random Forest, along with data preprocessing and evaluation tools for accuracy and F1 score metrics. Built in Rust.
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Harbinger: A time series forecasting model developed with the Burn deep learning framework in Rust. Utilizes LSTM (Long Short-Term Memory) networks to predict stock prices from historical data. Built in Rust.
Outside of work, I enjoy:
- Experimenting with sourdough bread 🍞
- Competing in CrossFit 🏋️♂️
- Watching American football 🏈
- Traveling to remote locations 🌍