I am Simen, a data scientist with a solid foundation in Python, machine learning, natural language processing, and data visualization. I enjoy turning complex data into actionable insights and building predictive models that forecast trends and inform decisions. I’m comfortable leading projects and collaborating with cross-functional teams to deliver results.
Beyond my technical work, I value customer experience and a positive, inclusive team culture. I have led teams, managed operations, and fostered environments where diverse staff can grow and stay motivated. I’m excited to continue learning and contribute to a dynamic organization that values curiosity, collaboration, and impact.
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I built a full-stack, AI-powered agriculture dashboard designed to help farmers optimize the harvesting of premium fruits. The system combines drone-based computer vision with a web dashboard to identify fruit types, assess ripeness, and predict optimal harvest dates. Using aerial images captured by a drone, a Python-based AI model detects individual fruits, determines whether they are ready to be plucked or will be ready within a few days, and sends precise GPS locations to the dashboard.
The platform allows farmers to visualize fruit readiness on a map, estimate expected yield, and calculate labor requirements by predicting how many workers are needed for harvesting at specific times. The application was built using JavaScript for the frontend, Tailwind CSS for UI design, Python for AI and backend logic, and SQLite for data storage, with API integrations connecting the AI model, database, and dashboard in real time. The result is a data-driven decision tool that reduces waste, improves harvest timing, and increases operational efficiency for farmers.
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