Catastrophe Risk Analyst

Berkshire Hathaway Specialty Insurance Company; Greater London; On-site; GBP 60,000 - 90,000; Full time

Benefits offered by this job

Competitive package

Meaningful career growth opportunities

Dynamic, action-oriented environment

Job summary

Berkshire Hathaway Specialty Insurance (BHSI) in London is seeking a Catastrophe Risk Analyst to join the CAT E&A team. You will evaluate catastrophe exposures across perils using proprietary models and communicate results to underwriters.

You will develop new parametric solutions, analyse meteorological data, and advance catastrophe modelling and data science techniques in collaboration with colleagues across locations.

Qualifications

• BSc or MSc in meteorology, atmospheric science, natural or environmental sciences, or a related field.
• Proficiency in Python, R or MATLAB.
• Working knowledge of probability, statistics or data science.

Responsibilities

• Utilize proprietary and market catastrophe models to evaluate accounts and develop insights for quotes for catastrophe risks.
• Design parametric insurance solutions (FastCAT) and communicate modelling results to underwriting.
• Perform data analysis on meteorological and claims data to improve internal risk models.
• Develop expertise in catastrophe modelling and data science techniques and apply to atmospheric perils.
• Assist with research and development to design catastrophe models for atmospheric perils and new products.

Skills

Programming languages

Probability & statistics

Data science concepts

Education

BSc or MSc in meteorology, atmospheric science, natural or environmental sciences

Job description

We are a values-based organization where respect, integrity, excellence, collaboration, and passion define who we are and how we do business.We value diversity of backgrounds, experience, and perspectives and strive to foster an inclusive environment that enables all our team members to bring their best selves to work.We are one team committed to building a culture where every teammate has the opportunity to contribute and be recognized. Want to be part of the team building the finest property, casualty and specialty lines insurance company in the world?

Learn more about our unique culture and history.

Job Opportunity:

Berkshire Hathaway Specialty Insurance (BHSI) has an exciting opportunity for a Catastrophe Risk Analyst to join the Catastrophe Engineering and Analytics (CAT E&A) team in our London office. The CAT E&A group is an innovative and versatile technical team conducting catastrophe risk research and development and providing complex quantitative metrics that inform underwriting decisions. The successful candidate will join the team responsible for the risk assessment of insured exposures across multiple perils. Your primary duties will involve calculating risk metrics for atmospheric perils and communicating these results to underwriters. As you grow in this role, you also contribute to the research and product development of traditional indemnity and parametric insurance solutions for new atmospheric perils.

Duties & Responsibilities:

• Utilizing proprietary and market catastrophe models to evaluate insurance accounts and develop insights for a diverse range of requests for quotes for catastrophe risks such as, but not limited to, tropical cyclones, severe convective storms, floods, wildfires, earthquakes, cyber etc.
• Design parametric insurance solutions (FastCAT) that are responsive to the needs of our customers, and communicate modelling results and structuring decisions to our underwriting team.
• Perform data analysis on a wide range of data sets (e.g., meteorological observations, insurance claims data, hazard models) to help improve our internal risk models.
• Develop and maintain expertise in catastrophe modelling and data science techniques, and their application to understanding risk.
• Assist with research and development to design catastrophe models for atmospheric perils and help to bring new products to market.

Qualifications, Skills and Experience:

Required

• BSc or MSc in meteorology, atmospheric science, natural or environmental sciences, or a related field. This role requires a robust understanding of atmospheric science, and ideally modules taken should reflect this (e.g., atmospheric physics/dynamics, or related classes).
• Proficiency in a programming language (Python, R, or MATLAB preferred).
• Working knowledge of probability, statistics, or data science.

Preferred

• Experience using large datasets to investigate research questions in atmospheric science. Demonstrated experience conducting independent research and data analysis (e.g., thesis/dissertation project) is a plus.
• Previous experience analyzing meteorological datasets such as numerical weather prediction model output, reanalysis model data, or observational measurements (e.g., remote sensing or instrumentation data), and an understanding of the benefits and limitations of different data sources.
• Knowledge of and experience using advanced data techniques such as machine learning, neural networks, extreme value theory, Bayesian statistics, or time-series analysis.
• Strong communication skills and an ability to explain technical concepts in a clear and easy to understand manner for both technical and non-technical audiences.
• A collaborative mindset and willingness to work with team members in different locations/time zones

BHSI Offers:

• A company with a truly unique opportunity and value proposition in the marketplace.
• A competitive package and meaningful career growth opportunities.
• A dynamic, action-oriented, and thoughtful environment centered on always doing the right thing for our customers, teammates and our other stakeholders.
• A purposely non-bureaucratic organization that embraces simplicity over complexity and emphasizes individual excellence in a team framework.

NOTE: Compensation will be commensurate with experience. This job description is not intended to be all-inclusive. Team Member may perform other related duties as negotiated to meet the ongoing needs of the organization.