A Day in the Life In this role, you will work on the development and application of technical workflows for analyzing environmental data, including downscaled climate model outputs. Your focus will be on developing climate projections for various weather phenomena (e.g., precipitation, temperature, snow) and assessing both current and future exposure risks. You will use tools and analytical methods to address challenges in climate datasets and support quantitative analysis related to exposure, vulnerability, risks, and resilience concerning long-term climate change for clients, including municipalities and infrastructure agencies. Your responsibilities will include preparing documentation that clearly summarizes methodologies and results for both technical and general audiences, ensuring accessibility and understanding. As part of a diverse and expert team, you will work collaboratively on multiple projects, ensuring commitments are met through effective coordination with internal colleagues, external agencies, and consulting team partners. You will contribute to advancing the Climate Risk & Resilience Services practice by providing data-driven analysis and decision-making. Additionally, you will participate in quality control activities for the climate analysis sections of our projects and help define best practices to maintain consistency and scientific rigor in our climate change risk assessments. You will also engage in research and development initiatives, helping to build innovative practices within the field of climate change risk and resilience. Collaboration is key, and you will work closely with national business lines within WSP, focusing on advisory services related to climate science, climate risks, and adaptation planning. Qualifications Hold an undergraduate or graduate degree in data science, hydrology, meteorology, atmospheric science, climate science, environmental engineering, or a related field. Possess strong computer skills, including programming skills (e.g., Python) and data management skills related to model outputs (e.g., familiarity with NETCDF file formats). Are proficient in version control systems (e.g., Git, GitHub) for managing code and collaborating on projects. Have experience with tools and coding scripts for effective data processing, analysis, and visualization. Have worked on coding projects and adapted scripts written by colleagues, with a strong grasp of standard programming practices. Are experienced with high-performance computing (HPC) and parallel processing in cloud environments (e.g., AWS, Google Cloud, Azure). Have a solid background in statistics, particularly statistical methods for meteorological data infilling and trend analysis. Have experience with climate change models and data portals, ideally with expertise in statistical and dynamical downscaling. Experience with AI and machine learning is a plus. Understand frequency analysis of extreme climate events (e.g., extreme rainfall, IDF curves) and hazard modeling approaches using climate data (e.g., hydrologic modeling, flood modeling, wildfire modeling). Are skilled in conducting climate-related vulnerability and risk assessments. Can effectively communicate technical analysis and results to non-technical audiences through data visualization and maps. Possess attention to detail, a commitment to quality reviews, and a focus on accuracy and excellence. Are innovative, capable of producing tailored products for clients, and enjoy working independently or collaboratively on remote projects. Thrive on new challenges and are eager to grow professionally, enjoying collaboration at both national and international levels. J-18808-Ljbffr
