Associate Director - Agricultural Modeling

Howden•Remote - Massachusetts, MA

12d•$100,000 - $145,000

About The Position

Howden Re is seeking an Agriculture Modeler to join its catastrophe analytics team and help develop advanced solutions for the U.S. crop insurance and reinsurance markets. The role is suited to a quantitatively oriented scientist with a background in physics, mathematics, statistics, engineering, data science, agricultural economics, or a related technical discipline. The successful candidate will work across agricultural modeling, including data preparation and validation, portfolio analysis and postprocessing, reporting, visualization, and mapping. They will develop crop yield models and stochastic simulation frameworks, and build in-season forecasting models using weather, climate, remote sensing, vegetation, soil moisture, and other agricultural data. The role also involves improving analytical processes, collaborating with internal and external stakeholders, and presenting findings and responding to client questions about exposure data, model validation, risk, portfolio profitability, and optimization. The expected base salary range is $100,000–$145,000. The range and ultimate title depend on relevant experience and location. This range excludes other compensation such as discretionary bonuses and benefits. Howden describes its culture as supportive of work-life balance, career progression, sustainability, and volunteering, and encourages new ideas and contributions to the company, industry, and wider community.

Requirements

At least 4 years of research and quantitative modeling experience developing statistical, predictive, and/or simulation models.
High proficiency in data analysis, manipulation, and visualization tools, with a strong programming background; Python and/or R preferred.
Ability to independently formulate research questions and execute analytical studies.
Strong organizational skills, including the ability to manage multiple tasks and projects simultaneously in a fast-paced, results-driven environment.
Excellent oral and written communication skills, including the ability to explain technical concepts succinctly to non-technical audiences.
Bachelor’s degree or advanced degree in physics, mathematics, statistics, engineering, or a related technical discipline.
Legally authorized to work in the United States.

Nice To Haves

An advanced degree in physics, mathematics, statistics, engineering, or a related technical discipline is preferred.
Knowledge of the U.S. crop insurance market.
Experience with optimization techniques.
Experience working with weather and climate datasets.

Responsibilities

Execute agricultural modeling work, including data preparation and validation, portfolio analysis and postprocessing, reporting results, data visualization, and mapping.
Develop crop yield models for major U.S. crops, including corn, soybeans, wheat, cotton, sorghum, rice, and specialty crops.
Design stochastic yield simulation frameworks using probabilistic techniques and implement machine-learning, statistical, and hybrid approaches for yield prediction and risk assessment.
Develop in-season crop yield forecasting models using weather observations, climate forecasts, remote sensing data, vegetation indices, soil moisture measurements, and other agricultural datasets.
Improve analytical processes to increase efficiency and deliver better results for clients.
Work with internal and external stakeholders to address client and market needs.
Present results and respond to questions about exposure data, real-time updates, model validation, view of risk, portfolio profitability, and optimization.
Independently formulate research questions and conduct analytical studies.