Demo

Senior Scientist I

Insurance Services Office, Inc.
Boston, MA Full Time
POSTED ON 1/16/2025
AVAILABLE BEFORE 4/2/2025

Company Description

While professional experience and qualifications are key for this role, make sure to check you have the preferable soft skills before applying if required.

We help the world see new possibilities and inspire change for better tomorrows. Our analytic solutions bridge content, data, and analytics to help business, people, and society become stronger, more resilient, and sustainable.

Job Description

Come join the Climate Statistics Team within the Research and Modeling Department at 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 team's projects 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, our modeling teams must carefully consider 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. For estimates of future risk, understanding and manipulation of climate model output must be married to our baseline model for climate risk in the present.

This is a fantastic position for a climate scientist or climate-oriented statistician with critical thinking and analytic skills pertaining to the modeling and analysis of climate impacts on atmospheric extremes. We hope to find candidates with either a solid command of the physical climate science or else the application of statistics to problems in atmospheric and climate sciences. Either way, we are looking for candidates with a collaborative mindset and 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 May Include :

  • Contribute to data analysis, physical interpretation, documentation, and statistical modeling 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.
  • Contribute reproducible analysis and analytic tools to our team Climate Statistics code bases.
  • 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.

Qualifications

Required Skills and Qualifications

  • Doctoral degree in Climate Science or Statistics, with demonstrated interest and experience in the other. (PhD is required; relevant post-doctoral or work experience may also be a plus but are not required).
  • Skills in data analysis, including ability and comfort in handling and intercomparing gridded climate model output data, as well as 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.
  • A love for coding and reproducible workflows.
  • 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)

  • 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, would be a major advantage.
  • Experience in collaborative coding under version control (e.g., git).
  • Experience with media interviews.
  • Expertise in the area of formal detection and attribution methodologies.
  • Proficiency in shell scripting and cluster computing.
  • Additional Information

    For over 50 years, Verisk has been the leading data analytics and technology partner to the global insurance industry by delivering value to our clients through expertise and scale. We empower communities and businesses to make better decisions on risk, faster.

    At Verisk, you'll have the chance to use your voice and build a rewarding career that's as unique as you are, with work flexibility and the support, coaching, and training you need to succeed.

    Verisk is recognized as a Great Place to Work for outstanding workplace culture in multiple countries. We value learning, caring and results and make inclusivity and diversity a top priority.

    Verisk Businesses

    Verisk provides a variety of solutions across different sectors including Underwriting Solutions, Claims Solutions, Property Estimating Solutions, Extreme Event Solutions, Specialty Business Solutions, Marketing Solutions, and Life Insurance Solutions.

    Verisk Analytics is an equal opportunity employer.

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