5 days left
- Sector Type
- Non-Government Organization/Non-Profit
Quantifying and communicating every American’s climate risk
The problem with climate risk today is that there is no accurate way for any individual or company to understand how climate change will impact them personally. We are solving this problem. In the last twelve months since we launched our revolutionary first risk product (FloodFactor.com), we have seen over 2 billion media impressions and millions of Flood Factor visits or API lookups.
First Street Foundation is a non-profit research and technology group. We have started a revolution in climate risk data. Our aspiration is to continue to update our flood model with the most recent data and methods to make our flood information even more valuable to Americans in understanding their personal climate risk. We are looking for an experienced Senior Hydrologist to accelerate our efforts in communicating hydrologic and climate science on an individual, property-specific level.
The Senior Hydrologist will work with the Data Science Team, within the larger Data Team, to develop, maintain, and operate the First Street Foundation Flood Model. The First Street Foundation Flood Model is a nationwide, climate-corrected 2D hydraulic flood model used to quantify risk at the property level and its outputs are shared publicly at FloodFactor.com.
This senior role will be responsible for incorporating new data and methods into the flood model and providing updated flood hazard layers to the rest of the Data Science team for the creation of property level statistics and incorporation into FloodFactor.com. Additionally, this role will stay up to date with the latest research in flood risk and engage with leading academic researchers and industry practitioners to publish new research. The Senior Hydrologist will then lead staff to creatively find ways to incorporate this work into our flood model.
- Lead operations of the hydraulic model to create flood hazard layers
- Identify new data sources for inclusion into the model and update hydrology data
- Conduct and publish research to advance the First Street Foundation Flood Model
- Represent First Street at scientific and professional conferences
- Create parallel processing workflows in both the cloud and on-premises hardware
- Lead model performance at scale through overseeing the creation of automated scripts built using C++, Python, SQL, Postgres, PostGIS, and others.
Experience / competencies
- Experience in hydraulic and hydrologic modeling platforms; experience with the LIS-FLOOD modeling framework is a plus.
- Ph.D. preferred, or M.S. with equivalent experience in a combination of hydrology and climatology
- Expertise in at least one of the following sources of flooding with familiarity in the rest - surge, fluvial, and pluvial.
- Professional Engineer or Professional Hydrologist preferred
- Expertise using scripted languages to efficiently and reproducibly create outputs (e.g. Python, C++. Matlab, SQL, and others)
- Expertise with big data analysis, parallel processing workflows, and cloud computing
- Strong understanding of probability and statistics in spatial processes
- Capability of executing with a high degree of concern for accuracy and reproducibility
- Excellent communications skills
- Ability to work in a fast-paced environment
Compensation & Benefits
- Competitive salary commensurate with experience
- Medical, dental and vision plans
- Generous paid time off, holidays and sick leave
- 12 weeks of fully paid parental leave
- Employer paid life insurance
- Tech startup environment and a new office space filled with cold brew and snacks
- Working on the world’s biggest issue with other passionate professionals
- Fun: Our profession is our passion
- Inclusive: Everyone has a voice
- Impact: We only do things that move the needle
- Trust: We rely on each other and the world can rely on us
- Integrity: We always consider the impact of our actions
We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.