Data Analytics Analyst

Job DescriptionJob Title: Data Analyst/ScientistLocation: RemoteDuration: 3+ years Experience 3-5 years of professional experience in data analytics or data science leveraging meteorological data sources (e.g., numerical weather prediction output, satellite imagery, weather station data) Proven experience working with large, complex meteorological datasets in a cloud-based environmentDemonstrated experience guiding a product from development to operationsDemonstrated experience troubleshooting data quality, pipeline, or ingestion issuesTechnical Skills & LanguagesProcessing data at scaleAbility to optimize processing of meteorological data to consume minimal time and memoryFamiliarity with cloud-optimized formats for raster data like ZarrCreating meteorological data visualizationsAbility to package meteorological output in a way that is understandable to a general audienceFamiliarity with static visualizations using Python and/or interactive visualizations using JavaScriptSQLFamiliarity with joins, CTEs, window functions, performance optimizationWriting and maintaining reusable, well-documented queriesAnalytics & VisualizationStrong understanding of how data structure impacts visualization performance and usabilityFamiliarity with common bottlenecks when rendering large datasets and their resolution (e.g., data binning, downsampling, efficient plotting methods and memory use) Understanding of meteorological variables in traditional numerical weather prediction and AI model output and the ability to identify those that may be correlated with utility operationsSoft Skills & Work StyleStrong analytical and problem-solving skillsAbility to work independently while collaborating with data engineers and internal SMEsClear written and verbal communication, especially when explaining data issues or findingsExperience prioritizing work across multiple projectsPreferred QualificationsBackground in Atmospheric Science or another Earth ScienceTechnical PreferencesExperience with Python for data analysis and transformationsExperience working with raster datasets in formats like GRIB, GeoTIFF, and NetCDFExperience with geospatial data and performance optimizations when working with geospatial data such as leveraging spatial indicesKnowledge of basic statistical concepts like correlation and trend analysis using methods like least-squares fittingFamiliarity with the concepts of using multiple threads and/or multiple CPUs to process large datasets quicklyExperience with version control (Git or similar) Basic understanding of data governance, lineage, or metadata managementDomain & Business ExperienceExperience in utilities, energy, infrastructure, or regulated industriesFamiliarity with operational, asset, or time-series dataExperience working with imperfect or operational source systemsProfessional AttributesAbility to translate business questions into efficient analytical datasetsDemonstrated attention to detail with a strong focus on data accuracy and reliability