Water Resources Data Scientist

Position Summary:
As a Water Resources Data Specialist, you will play a key role in the ingestion, processing, and analysis of weather and forecast datasets, utilizing NOAA products and numerical weather models such as WRF to support real-time forecasting and decision support systems. You will participate in engineering studies related to hydrology, hydraulics, and flood risk analysis, leveraging industry-standard modeling tools. Additionally, you will deploy and operate machine learning pipelines for streamflow, reservoir storage, and flood forecasting, ensuring the reliability and efficiency of critical water management systems.

Key Responsibilities:

• Ingest, process, and analyze weather, hydrologic, and operational data, including NOAA radar and forecast products, enhancing real-time forecasting capabilities.
• Conduct hydrologic, hydraulic, and risk assessments utilizing watershed, runoff, and 1D/2D hydraulic models.
• Support the deployment and maintenance of machine learning algorithms and analytical pipelines for flood and streamflow prediction.
• Maintain and troubleshoot software applications, databases, and telemetry systems related to sensor networks and alerts.
• Design and implement data pipelines for real-time data visualization and decision support.
• Collaborate with engineering teams on studies involving hydrology, hydraulics, and flood risk management, applying advanced modeling and analytical techniques.
• Assist in integrating complex model outputs into operational forecasting and decision-support tools, ensuring system accuracy and robustness.

• Bachelor s degree in civil/environmental engineering, hydrology, meteorology, atmospheric science, data science, computer science, or a related field. A Master s degree or higher in hydrology, hydraulics, water resources engineering, or hydro informatics is preferred.
• Minimum of 4 years of professional experience in environmental permitting, water supply planning, groundwater management, hydrogeology, or related fields.
• Proven experience with statistical, hydrologic, and hydraulic analyses, including watershed and hydraulic modeling.
• Strong knowledge of NOAA datasets, radar products, precipitation forecasts, and numerical weather prediction models like WRF.
• Proficiency in Python (Pandas, NumPy), Java, and experience developing APIs with frameworks such as Flask or Django; familiarity with Golang and React is advantageous.
• Experience with relational and non-relational databases, containerization (Docker), version control (Git), cloud platforms (AWS preferred), and RESTful API services.
• Familiarity with machine learning concepts applied to forecasting and analytics.
• Excellent analytical, communication, and collaboration skills.