Staff or Senior Staff Data Scientist - Resilience Modeling

- Build a global-scale resilience model to predict the societal, and economic impact and recovery of the built environment against disasters- Build and improve existing impact and recovery models (e.g., infrastructure vulnerability models)- Work with and support domain experts and data scientists in different hazard products.- Demonstrate up-to-date modeling techniques and apply this to the development, execution, and improvement of action plans- Assess the potential usefulness and validity of new approaches and data sources.- Identify key problems in prediction models and propose innovative solutions- Formulate your own problems as the problem might not always be defined for you- Collaborate with an interdisciplinary team of software engineers and data scientists on cross-functional projects, interpreting data, and translating it into actionable insights

Requirements

• Ph.D. (preferred) or Master’s degree in structural engineering, civil engineering, or a related field with 3+ years of experience in the industry.
• Strong background in statistics, machine learning, or quantitative analytics
• Advanced programming skills in python to develop models and support model updates
• Strong desire to learn new topics and skills and to develop innovative products

Preferred Qualifications

• Research experience in the latest fragility, resilience modeling, technical guidelines, etc.
• Experience in developing scalable and generalized models
• Deep understanding of stochastic event simulation frameworks
• Deep knowledge of power transmission and distribution system fragility
• Domain knowledge of natural disasters or risk modeling
• Strong publication record