Weather Data Scientist (3/2 Hybrid Work Schedule)

Responsibilities: 

Forecasting Model Improvements: 

• Conduct in-depth research on weather modeling and forecasting. 

• Develop and refine quantitative models to improve weather predictions. 

• Collaborate with cross-functional teams to integrate research findings into operational models. 

• Enhance CCI’s AI Weather Forecasting capabilities. 

• Increase the spread and accuracy of our forecasting models. 

• Implement machine learning techniques to capture actual weather conditions and improve forecast reliability. 

Global Weather Coverage: 

• Specialize in weather patterns and forecasting for the US and Europe. 

• Stay updated on global weather trends and incorporate them into forecasting models. 

• Provide expert insights on weather-related events and their potential impacts. 

Weather Data Ingestion: 

• Manage the ingestion of large-scale weather data, approximately 3 billion rows daily. 

• Ensure data accuracy, quality, and integrity for analysis and modeling. 

• Develop efficient data processing pipelines to handle massive data sets. 

Time Series and Machine Learning: 

• Apply time series analysis techniques to weather data. 

• Utilize machine learning algorithms to identify patterns and improve forecast accuracy. 

• Continuously monitor and evaluate model performance, making necessary adjustments. 

Qualifications: 

• Bachelor’s degree in Meteorology, Atmospheric Science, Data Science, or a related field. 

• Minimum of 3 years of experience in weather modeling and forecasting, with a strong quantitative background. 

• Proficiency in machine learning, time series analysis, and statistical modeling. 

• Experience working with large-scale data sets and data ingestion processes. 

• Strong programming skills in Python, R, or similar languages. 

• Familiarity with AI and machine learning frameworks (e.g., TensorFlow, PyTorch). 

• Excellent analytical and problem-solving abilities.