Data Scientist - Resilience Modeling
Menlo Park
Applications have closed
One Concern
Our mission is to make disasters less disastrous. We integrate hazard science with cutting edge AI/ML to help customers uncover their blindspots, and make better decisions. %
One Concern is a Menlo Park-based benevolent artificial intelligence company with a mission to increase the global community's resilience to natural hazards. Founded at Stanford University, One Concern enables cities, corporations, and citizens to embrace a disaster-free future through AI-enabled technology, policy, and finance. By combining data science and natural phenomena science we are pursuing a vision for planetary-scale resilience, where everyone lives in a safe, equitable, and sustainable world.
One Concern is growing rapidly and we are looking for a passionate and motivated Data Scientist for Resilience Modeling to join our team.
One Concern is growing rapidly and we are looking for a passionate and motivated Data Scientist for Resilience Modeling to join our team.
What you will do
- Build a global-scale resilience model to predict the societal, 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 into actionable insights
Must-haves
- Ph.D. (preferred) or Master’s degree in operation research, structural engineering, statistics or related field
- Strong background in statistics, machine learning, and quantitative analytics
- Advanced programming skills in python (preferred) or R to develop models and support model updates
- Strong desire to learn new topics and skills and to develop innovative products
Good to have
- Experience in developing fragility, vulnerability or recovery models of infrastructure systems or buildings
- Domain knowledge of natural disasters or risk modeling.
- Experience in developing machine-learning models and/or statistical/probabilistic models
- Strong publication record
Tags: Engineering Finance Machine Learning Python R Research Statistics
Region:
North America
Country:
United States
Job stats:
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Category:
Data Science Jobs
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