First Street needs to ingest, process, and analyze climate risk and ancillary data to develop data pipelines, query geospatial databases, calculate statistics, implement QA/QC processes, utilize geographical imagery, and develop machine learning and AI models to quantify the impacts of climate, property by property.
Requirements
- Experience with the design, and use of databases, such as PostgreSQL
- Proficiency with Python to efficiently and reproducibly analyze complex datasets preferred. Additional languages like SQL and R also required
- Experience with writing software to efficiently process and analyze with geospatial data using open source tools
- Strong understanding of probability and statistics as applied to spatial data
- Expertise using scripted languages to build data pipelines on both local and cloud-based systems
- Experience with big data analysis, parallel processing, and batch/spot workflows on cloud platforms including AWS, GCP, and/or Azure
- Proficiency with source control platforms such as Git
Responsibilities
- Provide technical support in the processing, analysis, and interpretation of geospatial observations and modeling data.
- Develop and implement processes for processing large volumes of hazard prediction data to improve risk assessment quality and accuracy.
- Plan, execute and direct Unix-based workflows on local and cloud-based clusters, using GDAL, PostgreSQL, Python and related technologies.
- Analyze raster and vector data at scale to improve model accuracy, identify quality control issues, and develop suggested remedies for identified issues.
- Perform statistical analysis to validate hazard model predictions and assess model uncertainties.
- Design and implement quality assurance checks on the climate risk data and derived statistics
- Assist in resolution of customer support issues through quality control checks and explanation of the models and risk statistics
Other
- 5+ year of professional experience
- A science-based approach with a high degree of concern for reliability, accuracy and reproducibility
- Experience in GIS and/or geospatial statistical analysis
- Previous experience in the physical sciences
- Hybrid Schedule with in-office work days on Monday, Wednesday and Thursday
