First Street · 3 days ago

Data Analyst

New York, NY

Full-time

Onsite

Entry Level

1+ years exp

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Environmental ConsultingNon Profit

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Responsibilities

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.

Qualification

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Data OperationsGIS KnowledgeProgrammingSQL QueriesPythonRProbabilityStatisticsScripted LanguagesData PipelinesBig Data AnalysisParallel ProcessingCloud PlatformsAWSGCPAzureSource ControlGitReproducibilityGeospatial Statistical AnalysisMasters DegreePhysical Sciences Experience

Required

Bachelor's Degree in Data or Climate Science, or a related Field

1+ 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