One Concern
Menlo Park
51-200 employees
We're advancing science and technology to make disasters less disastrous.
Staff or Senior Staff Data Scientist - Resilience Modeling
Staff or Senior Staff Data Scientist - Resilience Modeling
This job is no longer open
- 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
$143,000 - $208,000 a year
Open to a Staff Engineer or Senior Staff Engineer for this role. Leveling will be determined in the interview process.
This job is no longer open