Lead Hazard Scientist

Overview

Position Summary:

The Lead Hazard Scientist is responsible for driving Mercury’s evolving understanding of extreme weather and climate-related catastrophe risk. This role leads applied scientific research to support pricing, underwriting, and reinsurance strategy for perils such as wildfires, urban conflagrations, fire-following earthquakes, severe convective storms, and hurricanes. Working as part of a multidisciplinary team, the Hazards Scientist will translate cutting-edge science into insurance-relevant tools, models, and insights.

 

Geo-Salary Information

State specific pay scales for this role are as follows:

$118,465 to $224,994 (CA, NJ, NY, WA, HI, AK, MD, CT, RI, MA)

$107,695 to $204,540 (NV, OR, AZ, CO, WY, TX, ND, MN, MO, IL, WI, FL, GA, MI, OH, VA, PA, DE, VT, NH, ME)

$96,926 to $184,806 (UT, ID, MT, NM, SD, NE, KS, OK, IA, AR, LA, MS, AL, TN, KY, IN, SC, NC, WV)

The expected base salary for this position will vary depending on a number of factors, including relevant experience, skills and location.

Responsibilities

Essential Job Functions: 

• Lead and independently contribute to original research and synthesize findings from the broader scientific community on the physical drivers of natural catastrophes, including their climate variability, long-term trends, and spatial patterns across Mercury’s footprint.

• Partner with catastrophe scientists and lead risk assessments using both third-party platforms (e.g., Verisk-AIR, Moody’s-RM, KCC, etc.) and by developing proprietary models to improve loss assumptions and hazard views.

• Lead and independently contribute to the development of scientific datasets, event catalogs, and physical hazard frameworks tailored to insurance and reinsurance applications.

• Lead and independently contribute to the analysis of extreme weather and climate datasets to produce climate-conditioned views of risk and forward-looking hazard projections.

• Lead technical validation of vendor risk scores and support internal benchmarking efforts using policy-data, claims, and other proprietary datasets.

• Lead cross-functional collaboration with Actuarial, Product, Underwriting, and R&D teams to ensure scientific rigor in pricing and capital allocation decisions.

• Drive internal education, white papers, and occasional public-facing insights to strengthen Mercury’s position as a leader in climate and catastrophe science.

• Lead and develop reports, presentations, and data visualizations to effectively communicate findings to technical and non-technical teammates.

• Lead and develop real-time risk analytics and detailed loss estimates to assess event impact.

• Lead the refinement of model assumptions by testing adjustments to event frequency, vulnerability curves, and loss scaling to incorporate proprietary insights and market expertise.

• Remain at the forefront of scientific advancements in event simulation, hazard characterization, and high-resolution modeling of natural perils.

• Represent Mercury in external research collaborations, industry working groups, and technical forums.

 

 

Qualifications

Education: 

Ph.D. or equivalent combination of education and experience is required with an emphasis in natural or physical sciences such as meteorology, atmospheric science, environmental science, earth systems science, oceanography, climate science, applied physics, applied mathematics, engineering, remote sensing, geoscience, hydrology, geophysics, computer science, or a closely related discipline.

Preferred:

Ph.D. with an emphasis an emphasis in natural sciences and a concentration in wildfire, severe convective storms, and/or tropical cyclones

 

Experience:

5-Years + Ph.D. or equivalent combination of education and experience

Preferred: 

10-Years + Ph.D 

 

Knowledge and Skills:

Minimum: 

• Expert technical background with direct application to quantifying the probability, severity, and spatial characteristics of extreme weather and climate-related events.

• Expertise working with large-scale weather, climate and hazard datasets (e.g., ERA5, NARR, HRRR, HAZUS, MTBS, FPA-FOD, LANDFIRE, GRIDMET, MODIS, NCEI Storm Events Database, SPC Storm Reports, CMIP6, LOCA, CORDEX, IBTrACS, NEXRAD, MRMS, SLOSH, HURDAT2) to analyze physical drivers of risk.

• Experience working within an insurance, reinsurance, catastrophe modeling firm, consulting firm, or similar environment.

• Expertise with statistical modeling, machine learning, or downscaling methods applied to natural hazards or climate risk.

• Expert knowledge of extreme weather perils such as wildfire, severe convective storms, and hurricanes and familiarity with associated event simulation techniques.

• Expertise translating complex scientific findings into actionable insights for use in pricing, underwriting, exposure management, and reinsurance decisions.

• Expert programming and data analysis skills using tools such as Python, R, or similar and experience with geospatial libraries and data pipelines.

• Clear and concise communication skills, with proven ability to collaborate effectively across interdisciplinary teams and engage with both technical and business stakeholders.

• Highly motivated and driven individual with excellent critical thinking and problem-solving skills.

• Proactive mindset with experience in strategic planning and a strong sense of ownership; capable of driving research and directing multiple project streams with competing priorities and delivering high-quality outputs independently.

• Demonstrated passion to contribute to a growing scientific capability within a primary insurance context and engaging in cross-sector collaboration with academia, vendors, and the re/insurance market.

• Ongoing learning on the latest scientific research, modeling techniques, and industry trends.

• Collaboration is key; lead partnerships with Actuaries, Research and Development, State Product Management, Underwriting, and other stakeholders to translate catastrophe risk assessments into effective business decisions.

 

Preferred: 

• Experience with catastrophe modeling platforms (e.g., Verisk-AIR, Moody’s-RMS, KCC, etc), with ability to interpret and critique hazard and vulnerability assumptions.

• Experience developing or refining hazard footprints, stochastic event sets, or scenario-based views of risk for insurance applications.

• Quantitative skills and experience calculating metrics like Average Annual Loss (AAL), Exceedance Probability (EP), Value at Risk (VaR), Tail Value at Risk (TVaR), and other standard measures.

• Experience in programming languages and tools like SQL, NumPy, Pandas, SciPy, Dask, PySpark, etc.

• Experience with advanced modeling techniques including artificial intelligence as applied to extreme weather datasets.

• Experience with downscaling techniques in dynamical weather models.

• Experience in applying advanced quantitative methods to measure and analyze insurance catastrophe risk.

• Experience in catastrophe risk management including rating, underwriting, and reinsurance.

 

Pay Range

USD $118,465.00 - USD $224,994.00 /Yr.