Data Quality Analyst
New York City
First Street
We exist to make the connection between climate and financial risk at scale for financial institutions, companies and governments.Who we are: First Street is the standard for Climate Risk Financial Modeling. We use transparent and peer-reviewed methodologies to calculate the past, present, and future climate risk for every property in the world. We started working with the world’s leading climate scientists to create groundbreaking, climate-adjusted, property specific models over 8 years ago and haven’t stopped.
Our mission: We exist to connect climate and financial risk.
Our data: We create physics-based, deterministic models of flooding, wildfire and hurricanes, and advanced statistical models of extreme heat, air quality, drought, hail, severe convective storms, winter storms, and more. All of this data is used to create property-level financial risk metrics and macroeconomic variables to quantify the impacts of climate, property by property.
Our customers: We empower governments at the highest levels to make smart regulations, businesses to avoid bad investments, and everyday Americans to understand their personal risk from climate change. We are relied on every day by:
Agencies ranging from the U.S. Department of Treasury to Fannie Mae
The world's biggest banks such as Bank of America and Wells Fargo
Institutional investors like Nuveen and Blackstone
Millions of everyday users on Zillow, Redfin, Realtor.com, Homes.com, and more
We believe: With the right data, we can identify the problems, avoid bad investments, and implement solutions. This is why we have invested tens of millions of dollars into our science, data, people, and products and have raised tens of millions more to move even faster. Read more about our culture here and see what Climate Risk Financial Modeling is all about here.
Come join us and use your talents to change the world.
Team & Role Overview:
We’re looking for our first dedicated Data Quality Analyst to join our growing team in New York City. You’ll be responsible for ensuring the accuracy, reliability, and performance of our climate risk products. This is a hybrid role - you need to be strong in validating and stress-testing datasets and also comfortable with software QA. You’ll work at the intersection of software, data, and product—ensuring that our data-driven outputs are trustworthy, especially as we scale our financial risk metrics.
This is a hybrid role with in-office presence required on Monday, Wednesday, and Thursday.
What you’ll do:
Define and refine acceptance criteria in collaboration with product, engineering, and data science teams to ensure clarity and testability
Deeply understand our datasets, focused on financial and climate risk data—to identify edge cases, anomalies, and potential failure points
Create test plans and test cases that stress the system under real-world and corner-case conditions
Design and run manual exploratory tests for complex features, using First Street’s Enterprise Suite, especially where automated coverage is limited
Develop and maintain a comprehensive test portfolio, including unit, integration, regression, and end-to-end tests across both product and data workflows
File clear tickets, providing clear documentation and context for the data and engineering team
What you’ll need:
3+ years of experience as a Data Quality Analyst or Data Analyst
Proven experience working with data-centric applications or financial datasets with 100’s of millions of data points
Hands-on experience with validating APIs, data transformations, and large-scale datasets
Comfort working with basic SQL queries and using scripting languages to analyze large CSVs.
Excellent attention to detail, communication skills, and a bias for action
Ability to work hybrid in NYC three days per week
What will make you stand out:
Background in climate science, geospatial data, or financial risk modeling
Experience being the first data QA hire or building data QA systems from scratch at a startup
Experience with Python + Pandas/Polars, or R + dplyr a plus
Proficiency in modern testing frameworks (e.g., Playwright, Jest, or similar)
Familiarity with CI/CD tools (e.g., GitHub Actions, CircleCI)
Experience building automated QA pipelines that integrate with CI/CD processes to ensure consistent, reliable deployments
Passion for our mission to connect climate and financial risk
How we work:
Impact: We only focus on things that move the needle
Drive: We are driven by the role we play in connecting climate and financial risk
Ownership: This is our company and we act accordingly
Urgency: We move quickly because the world depends on it
Resilience: We have a growth mindset in all that we do
What we offer:
Competitive salary commensurate with experience
Ownership interest in the company via Employee Stock Option Plan
Hybrid Schedule with in-office work days on Monday, Wednesday and Thursday
15 vacation days along with 8 statutory company holidays, 5 days for winter break office closure, 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
Life Insurance
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.
* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰
Tags: APIs CI/CD Data QA Data quality Engineering GitHub Pandas Physics Pipelines Playwright Python R SQL Statistics Testing
Perks/benefits: 401(k) matching Career development Competitive pay Equity / stock options Health care Insurance Medical leave Parental leave Snacks / Drinks Startup environment
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