Insurance Computer Science Jobs in Milton, MA (NOW HIRING)

Join Verisk Catastrophe and Risk Solutions and contribute to the development of cutting-edge machine learning models for climate risk.  You will play a critical role in expanding our modeling capabilities to improve predictions of weather extremes and enhance the risk insights we deliver to clients.  In this role, you will be responsible for building, deploying, and validating machine learning algorithms to solve real-world climate problems, contributing to the development of stochastic event catalogs for perils such as winter storms, storm surge, tropical cyclones, and other natural hazards.  This role is a perfect blend between machine learning and climate science, and your work will directly impact how insurers, reinsurers, and governments prepare for and respond to catastrophic events. 

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. 

For the eighth consecutive year, Verisk is proudly recognized as a Great Place to Work for outstanding workplace culture in the US, the fourth consecutive year in the UK, Spain, and India, and the second consecutive year in Poland. In addition, we've been recognized by The Wall Street Journal as one of the Best-Managed Companies and by Forbes as a World's Best Employer, testaments to the value we place on workplace culture.

We're 7,000 people strong.  We relentlessly and ethically pursue innovation. And we are looking for people like you to help us translate big data into big ideas. Join us and create an exceptional experience for yourself and a better tomorrow for future generations.

 Verisk Businesses

Underwriting Solutions - provides underwriting and rating solutions for auto and property, general liability, and excess and surplus to assess and price risk with speed and precision

Claims Solutions - supports end-to-end claims handling with analytic and automation tools that streamline workflow, improve claims management, and support better customer experiences

Property Estimating Solutions - offers property estimation software and tools for professionals in estimating all phases of building and repair to make day-to-day workflows the most efficient

Specialty Business Solutions - provides an integrated suite of software for full end-to-end management of insurance and reinsurance business, helping companies manage their businesses through efficiency, flexibility, and data governance

Catastrophe and Risk Solutions - provides risk modeling solutions to help individuals, businesses, and society become more resilient to catastrophic events.

Marketing Solutions - delivers data and insights to improve the reach, timing,relevance, and compliance of every consumer engagement

Life Insurance Solutions - offers end-to-end, data insight-driven core capabilities for carriers, distribution, and direct customers across the entire policy lifecycle of life and annuities for both individual and group.

Verisk Maplecroft - provides intelligence on sustainability, resilience, and ESG, helping people, business, and societies become stronger

Verisk Analytics is an equal opportunity employer.

Verisk invests in a benefits package for all employees that includes the following: Health Insurance, a Retirement Plan, Disability benefits, and a Paid Time Off program. We offer a competitive total rewards package that includes base salary determined based on role, experience, skill set, and location.

All members of the Verisk Analytics family of companies are equal opportunity employers. We consider all qualified applicants for employment without regard to race, religion, color, national origin, citizenship, sex, gender identity and/or expression, sexual orientation, veteran's status, age or disability. Verisk's minimum hiring age is 18 except in countries with a higher age limit subject to applicable law.

https://www.verisk.com/company/careers/

Unsolicited resumes sent to Verisk, including unsolicited resumes sent to a Verisk business mailing address, fax machine or email address, or directly to Verisk employees, will be considered Verisk property. Verisk will NOT pay a fee for any placement resulting from the receipt of an unsolicited resume.

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    Ph.D. degree (completed or close to completion) in computer science, statistics, physics, engineering, atmospheric sciences, or a related field. 
    Strong background in machine learning for spatio-temporal data and physical processes.
    Theoretical understanding of fluid dynamics and climate processes.
    Proficiency in Python and ML libraries (such as PyTorch or Jax) as well as version control (Git). 
    Experience with climate data (e.g., reanalysis, satellite, or numerical weather prediction outputs).
    Familiarity with geospatial data processing and visualization tools (e.g., xarray, NetCDF, pandas). 
    High degree of comfort deploying machine learning models in HPC environments.
    Excellent verbal and written communication skills, including the ability to convey technical ideas to a non-technical audience. 
    Team-focused and evidence of supporting project team members.

#LI-ZP1
#LI-Hybrid

    Ph.D. degree (completed or close to completion) in computer science, statistics, physics, engineering, atmospheric sciences, or a related field. 
    Strong background in machine learning for spatio-temporal data and physical processes.
    Theoretical understanding of fluid dynamics and climate processes.
    Proficiency in Python and ML libraries (such as PyTorch or Jax) as well as version control (Git). 
    Experience with climate data (e.g., reanalysis, satellite, or numerical weather prediction outputs).
    Familiarity with geospatial data processing and visualization tools (e.g., xarray, NetCDF, pandas). 
    High degree of comfort deploying machine learning models in HPC environments.
    Excellent verbal and written communication skills, including the ability to convey technical ideas to a non-technical audience. 
    Team-focused and evidence of supporting project team members.

    Design, build, deploy, and maintain ML models to achieve research and business objectives.
    Collaborate with and provide support to other research groups to develop new machine learning tools and enhance existing models.
    Evaluate model performance on real-world data and present findings to stakeholders.
    Prepare, clean, process, and quality-control data used in modeling workflows.
    Collaborate with meteorologists, hydrologists, and engineers to integrate physical insights into ML models.