Leveraged my expertise in machine learning, deep learning, and data analytics to pioneer the development of an innovative AI-driven tool for short-term weather forecasting, with a specific focus on predicting hailstorms.
Targeted diverse spectrum of Japanese companies, primarily targeting the insurance and car dealership sectors, aimed at elevating risk assessment capabilities by providing exceptionally accurate forecasts. This enhancement in risk assessment holds particular significance for the insurance sector, where weather-related events can exert substantial financial implications.
Accomplishments:
Developed a Short-term Hail Nowcast prototype, surpassing the accuracy of the Japan Meteorological Agency’s (JMA) forecast system (72% vs. 55%).
Delivered a compelling Proof of Concept (PoC) to MS&AD insurance group, showcasing practical applications and superior forecasting capabilities.
Transferable Skills:
Analytical skills and Quantitative Analysis, Data visualization
Knowledge of Geneartive AI
Knowledge of Weather and Radar Meteorology.
Leadership, project management, and problem-solving skills.
Responsibilities:
Led a data science team, ensuring collaboration between data scientists and industry experts.
Mentor the junior team members and support them with technical issues.
Translated specific needs of stakeholders into an optimized deep learning model.
Challenges and Difficulties:
Required a deep understanding of meteorological data and generative deep learning techniques to provide accurate forecasts in a short time frame.
Feedback and Endorsements:
Positive feedback from stakeholders.
Context:
Comprehensive background in deep learning and data analytics.
Commitment to projects with direct business relevance, contributing to industry advancements.