Model Validation Analyst III

Model Validation Analyst III

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.