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
This role is focused on Extreme Event Risk Models, doing Quality Assurance on the models mentioned in the description and developed at Verisk.
- You will partner with scientists and structural engineers, and identify areas for model validation, with an emphasis on developing creative approaches to expand test coverage.
- Additionally, you will create detailed test plans and strategies to ensure the model has full QA coverage.
- You will ensure the products meet exacting requirements for accuracy and explicit and/or implicit validation of scientific, engineering, and financial algorithms.
- You will, under minimal supervision, be constantly manipulating and transforming data, performing advanced statistical analysis to validate complex model components, and summarizing findings to be presented at all levels of Verisk.
- You will author technical documents in Python’s Jupyter Notebook or in R Markdown detailing your validation work.
- You will participate in cross-functional Agile Scrum teams while delivering concurrent day-to-day tasks and using automated testing practices throughout the software development life cycle.
- Successful candidates will use their strong quantitative data analytics mindset to deliver strategic projects using robust methodologies.
- The position requires a strong commitment to quality assurance that leverages the best practices already in place and helps to enhance them.
Qualifications
- Candidates must have an undergraduate/graduate degree in STEM-related areas (data science, engineering, science, mathematics, finance, economics) as well as a graduate degree and 2 years of relevant work experience.
- Candidates must have experience in analytical programming, fluency in languages like Python or R, DB experience such as SQL, and knowledge of GIS tools, and libraries like Pandas, Tidyverse, and Data frames.
- Candidates must have experience working with large data sets performing analysis and manipulation.
- Experience with designing and/or validating numerical probabilistic models in engineering, science, catastrophe modeling, finance, actuarial science, etc.
- Candidates must have excellent attention to detail and experience with deriving actionable insights from data.
- Candidate must have excellent communication skills to interface with cross-functional teams.
- Prior experience with the AWS ecosystem and technology stack is preferable.
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Additional Information
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, fourth consecutive year in the UK, Spain, and India, and second consecutive year in Poland. We value learning, caring and results and make inclusivity and diversity a top priority. In addition to our Great Place to Work® Certification, 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 and Best Employer for Women, 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
Extreme Event Solutions — provides risk modeling solutions to help individuals, businesses, and society become more resilient to extreme events.
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
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.
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.
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