Machine Learning Scientist, Climate Modeling

Company Description

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

Join Verisk Extreme Event Solutions' research team and contribute to the development of cutting-edge AI models for climate risk. You will play a critical part in expanding our model capabilities to improve our understanding and predictions of climate extremes and enhance the view of risk we provide to our clients. In this role you will be responsible for building, deploying, and validating machine learning algorithms to solve real-world climate problems, focusing initially on storm surge and related sub-perils. This role is a perfect blend between machine learning and climate science, and you will find in it many opportunities to express your technical skills and creative mindset.

About The Day To Day Responsibilities Of The Role

• Design, build, deploy, and maintain machine learning models to achieve research and business objectives of the Research department.
• 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 key decision makers.
• Identify appropriate data sources and process, clean, and verify integrity of data used for analysis.
  

Qualifications

• Ph.D. degree (completed or close to completion) in computer science, statistics, engineering, or a related field.
• 2+ years of experience building machine learning models in industry or academia.
• Good theoretical understanding of the physical processes governing climate phenomena and fluid dynamics (turbulence, convection, closure models, etc.)
• Strong command of machine learning algorithms for spatio-temporal data and physical processes (LSTM, TCN, CNN, Transformers, PINNs, etc.)
• Experience with common data science toolkits such as scikit-learn, PyTorch or TensorFlow.
• High degree of comfort deploying machine learning models in a HPC environment. Experience with AWS a plus.
• 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.
  

Additional Information

Extreme event solutions at Verisk (formerly AIR Worldwide) provides risk modeling solutions that help individuals, businesses, and society become more resilient to extreme events. In 1987, Verisk founded the catastrophe modeling industry and today models the risk from natural catastrophes, supply chain disruptions, terrorism, pandemics, casualty catastrophes, and cyber incidents. Insurance, reinsurance, financial, corporate, and government clients rely on Verisk's advanced science, software, and consulting services for catastrophe risk management, insurance-linked securities, longevity modeling, site-specific engineering analyses, and agricultural risk management. Verisk's extreme event solutions team is headquartered in Boston, with additional offices in North America, Europe, and Asia. For more information, please visit www.air-worldwide.com. For more information about Verisk, a leading data analytics provider serving customers in insurance, energy and specialized markets, and financial services, please visit www.verisk.com.

At the heart of what we do is help clients manage risk. Verisk (Nasdaq: VRSK) provides data and insights to our customers in insurance, energy and the financial services markets so they can make faster and more informed decisions.

Our global team uses AI, machine learning, automation, and other emerging technologies to collect and analyze billions of records. We provide advanced decision-support to prevent credit, lending, and cyber risks. In addition, we monitor and advise companies on complex global matters such as climate change, catastrophes, and geopolitical issues.

But why we do our work is what sets us apart. It stems from a commitment to making the world better, safer and stronger.

It's the reason Verisk is part of the UN Global Compact sustainability initiative. It's why we made a commitment to balancing 100 percent of our carbon emissions. It's the aim of our "returnship" program for experienced professionals rejoining the workforce after time away. And, it's what drives our annual Innovation Day, where we identify our next first-to-market innovations to solve our customers' problems.

At its core, Verisk uses data to minimize risk and maximize value. But far bigger, is why we do what we do.

At Verisk you can build an exciting career with meaningful work; create positive and lasting impact on business; and find the support, coaching, and training you need to advance your career. We have received the Great Place to Work® Certification for the 7th consecutive year. We've been recognized by Forbes as a World's Best Employer and a Best Employer for Women, testaments to our culture of engagement and the value we place on an inclusive and diverse workforce. Verisk's Statement on Racial Equity and Diversity supports our commitment to these values and affecting positive and lasting change in the communities where we live and work.

Verisk Analytics is an equal opportunity employer.

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.

http://www.verisk.com/careers.html

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.

Consumer Privacy Notice

Effective November 15, 2021, and subject to applicable law, all prospective hires for this position will be required to demonstrate that they are fully vaccinated against COVID-19 by their start date, or qualify for a legally-required medical or religious accommodation to this vaccination requirement, as a condition of employment. Hired candidates who do not demonstrate that they are fully vaccinated against COVID-19 by their start date, and who have not been approved for a legally-required medical or religious accommodation will no longer meet the requirements for employment and their offers of employment will be immediately rescinded, in accordance with applicable law.