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Geospatial Data Engineer - Climate Change

First Street Foundation

First Street Foundation

Data Science
New York, NY, USA
Posted on Tuesday, May 21, 2024

Company & Mission Overview:

First Street is a research and technology company working to connect climate change to financial risk. First Street uses transparent, peer-reviewed methodologies to calculate the past, present, and future climate risk for every property in the United States. The data we create is made available in bulk format, API and through our Risk Factor product (riskfactor.com) for citizens, industry, and government.

Our data quantifies the impact of a warming planet at a property level, empowering governments to make smart regulation, businesses to avoid bad investments, and everyday Americans to protect their most valuable investment. We started seven years ago by working with the world’s leading climate scientists to create groundbreaking, climate-adjusted models and haven’t stopped.

Our data and tools are relied on every day by:

  • Government agencies ranging from the U.S. Department of Treasury to Fannie Mae
  • Financial institutions like Bank of America and Truist
  • States like South Carolina and Illinois
  • The millions of daily users on Redfin, Realtor.com, Allstate, and more.

And we’re just getting started. We believe that our work needs to match the pace and scope of the climate problem so we are investing tens of millions of dollars into our science, data, people, and products in order to increase our velocity and impact.

Come join us and use your talents to create solutions to address the problem.

Team & Role Overview:

We are looking for a Data Engineer with experience working with Geospatial Data to join our team. The successful candidate will be someone who deeply cares about the environment, loves information technology, and appreciates the importance of data for the success of the First Street mission. They will assist in the ingestion of climate risk and ancillary data from First Street modelers and data partners, develop data pipelines, query geospatial databases, calculate applicable statistics, implement Quality Assurance and Quality Control processes, utilize geographical imagery, and ensure that the Data Team’s databases and pipelines are coordinated and synchronized with the Software Engineering Team’s databases, APIs, and web services. This individual will be responsible for developing data operations across the Data Team, and through their expertise and leadership generally enabling all members of the Data Team to be successful in their roles.

What you’ll do:

  • Provide technical support in the processing, analysis, and interpretation of geospatial observations and modeling data.
  • Process large volumes of flood and wildfire risk 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 QGIS.
  • 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

What you’ll need:

  • Bachelor's Degree in Data or Climate Science, or a related Field
  • 2+ year of professional experience
  • Data operations: Experience with the design, maintenance, and use of geospatial databases, such as PostgreSQL
  • GIS knowledge: Experience with working with spatial data and GIS software such as QGIS
  • Programming: Proficiency with SQL queries to efficiently and reproducibly analyze complex datasets preferred. Additional languages like Python or R also required
  • 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
  • A science-based approach with a high degree of concern for reliability, accuracy and reproducibility
  • Experience in GIS and/or geospatial statistical analysis

What will make you stand out:

  • Previous experience in the physical sciences
  • Masters Degree Preferred

How we work:

  • Passion: We are driven by our shared goal to fight climate change
  • Inclusion: We believe the best decisions consider many points of view
  • Impact: We only focus on things that move the needle
  • Urgency: We move quickly because the world depends on it
  • Integrity: We use open science and operate transparently
  • Positivity: We are optimistic and enthusiastic in all that we do

What we offer:

  • Competitive salary ranges commensurate with experience, plus bonus based on personal and company performance (paid out 2x per year)
  • Ownership interest in the company via Employee Stock Option Plan
  • Hybrid Schedule with in-office work days on Monday, Wednesday and Thursday
  • Working time is flexible; core hours are 10:00am – 4:00pm
  • 15 vacation days along with 13 company holidays and 10 sick days
  • Health benefits covered at 100% for employee or a significant contribution for family plans
  • Vision and dental benefits with partial employee contribution
  • 12 weeks of paid parental leave
  • Access to One Medical, Teledoc, HealthAdvocate, Kindbody, and Talkspace
  • Company 401k program
  • Commuter benefits
  • Tech startup environment
  • Weekly team meals and an office stocked with coffee and snacks
  • Working on the world’s biggest issue with other passionate professionals

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.