[ES_JOBS_NET] Applied Climate Scientist job in Boston, MA

[Tolwinski-Ward, Suz]

APPLIED CLIMATE SCIENTIST
About the Role
Come join the Research and Modeling Team in Extreme Event Solutions at Verisk's Boston office, and contribute to building catastrophe models and products suited to address risk estimation in a changing climate.  Our department's development efforts offer opportunities for creative problem-solving, analysis, and communication at the interface of extreme weather, climate change, and risk. Catastrophe models depend fundamentally on quantitative description and simulation of the background climate states driving hazardous atmospheric activity. To produce unbiased estimates of today's risk, model proceed by careful consideration of the changes taking place over the length of the historical data, heavily supplemented by mechanistic physical reasoning where the statistics are uncertain, to represent the current climatology of natural hazards.
This is a fantastic position for a climate scientist with critical thinking and analytic skills pertaining to the modeling and analysis of climate impacts on atmospheric extremes. We hope to find candidates with a solid command of physical climate science, collaborative mindset, and a fearlessness for wading across disciplinary boundaries. The work in the position will contribute toward improvements in model-building to enable the (re)insurance sector to make better-informed decisions to bolster social resilience to a changing climate.
Day to Day Responsibilities

  *   Contribute to data analysis, physical interpretation, and documentation of climatic signals, trends and nonstationarities in atmospheric perils represented by Verisk's models. Signals of interest include those due to large-scale climatic modes, as well as those resulting from anthropogenically-forced activities
  *   Perform literature review and synthesis related to climatology and impacts of changing background environments on various perils
  *   Help interpret unfolding catastrophic events in the context of climatic variability and change
  *   Help formulate answers to client questions related to climatic aspects of Verisk Extreme Event Solution's atmospheric peril models
  *   Over time, come to act as a soundboard for teams building out models aiming for consistency with current climate state, as well as climate-change projected extensions of our model products
Required Skills and Qualifications

  *   Doctoral degree in Climate Science or closely related field required (PhD required; relevant post-doctoral or work experience may also be a plus but are not required)
  *   Data analysis, including ability and comfort in handling and intercomparing gridded climate model output data, as well as and sparse local observations with heterogeneity in space, time, and quality
  *   Strong interest in reviewing, understanding and explaining climatic change across a range of phenomena and regions
  *   Interest in interfacing and collaborating closely with a range of domain-area physical-scientists and statisticians within modeling teams
  *   Excellent communication in both technical and non-technical contexts, and formal presentations and informal discussions. Ability to create compelling data visualization to tell a story
  *   Current knowledge of CMIP models and scenarios
  *   Willingness and confidence to provide climate science leadership and guidance to team members; plus humility to admit when you don't have an answer and consult with other team members to find one
Bonus Skills (not strictly necessary, but presence of any would strengthen candidacy)

  *   Expertise in the area of formal detection and attribution methodologies
  *   Experience blending physical information with statistics to account for uncertainties in model and data
  *   Fluency with coding in R, and experience with R package development
  *   Experience with media interviews
  *   Proficiency in shell scripting and cluster computing

Official link to apply: https://jobs.smartrecruiters.com/Verisk/743999953024408-applied-climate-scientist?trid=1d68fb86-bf7b-4b74-9e40-9ec37cf43ea1



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