Quantitative Modeler / Analyst (Power Engineer)

  • Boston, MA, USA
  • Full-time
  • Verisk Business: Wood Mackenzie

Company Description

Wood Mackenzie is the global leader in data, analysis and consulting across the energy, chemicals, metals, mining, power and renewables sectors.

Founded in 1973, our success has always been underpinned by the simple principle of providing trusted research and advice that makes a difference to our customers. Today we have over 2,000 customers ranging from the largest global energy companies and financial institutions to governments as well as smaller market specialists.

Our teams are located around the world. This enables us to stay closely connected with customers and the markets and sectors we cover. Collectively this allows us to offer a compelling combination of global commodity analysis with detailed local market knowledge.

We are committed to supporting our people to grow and thrive. We value different perspectives and aspire to create an inclusive environment that encourages diversity and fosters a sense of belonging. We are committed to creating a workplace that works for you and encourage everyone to get involved in our Wellness, Diversity and Inclusion, and Community Engagement initiatives. We actively support flexible working and are happy to consider alternative work patterns, taking into account your needs and the needs of the team or division that you are looking to join. 

Hear what our team has to say about working with us:


We are proud to be a part of the Verisk family of companies! 

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 fifth 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.  

Job Description

The Quantitative Modeler / Analyst (Power Engineer) will be responsible for the development and maintenance of Genscape's model development effort and improvement program. Genscape's analytical models incorporate thousands of data parameters and detailed market information to model power flows and pricing based on key market drivers.

The Quantitative Modeler / Analyst will be responsible for developing new regional models for power markets. The successful candidate will also be responsible for upgrading existing models with new features, improved inputs, and more efficient programming.

In addition to the responsibility above, the Quantitative Modeler / Analyst is also responsible for project management and be a mentor of the junior modelers.


The candidate should be proficient in quantitative modeling techniques and have extensive experience in applying these techniques to complex model development. Must have experience in integer programming languages and linear models is required for this position.

The candidate should have a thorough understanding of energy markets gained by working in trading, capital project study, or economic planning environment. A Master’s degree in engineering, operations research, or statistics is desirable for the position.

The candidate should know the structure of the energy industry and its operation, especially the rules governing over-the-counter and exchange-traded energy markets, as well as the physical constraints on physical energy flows. Alongside heuristic power flow and dispatch modeling, the candidate should have background in statistical methods in forecasting input renewables and power demand.

Multiple years experience in programming languages similar to Python, C++, R, and mathematical solvers is an added benefit. Experience in database architecture is also desired.

The Quantitative Modeler / Analyst should have at least two years of experience in energy market analysis. The position requires at least three years of model/economic study experience.


Additional Information

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.


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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