Quantitative Analyst II

Essential Job Duties and Responsibilities

• Conduct advanced quantitative analysis using large structured and unstructured datasets

  from internal and external sources.

• Develop analytical solutions using R or Python, including model development, automation,

  and reproducible analytical workflows.

• Apply statistical learning, econometric modeling, and time-series analysis to identify

  trends, forecast outcomes, and support business decisions.

• Assist with additional analytical initiatives and cross-functional projects as required.

Knowledge, Skills, and Abilities

• Advanced knowledge of predictive modeling, statistical modeling, and econometric

  methods.

• Demonstrated programming ability in R or Python, including experience building 

  production-level analytical tools.

• Experience applying machine learning techniques such as regression models, classification

  methods, ensemble methods, or clustering.

Professional Competencies

• Strong organizational and project management skills.

• Ability to work independently while also contributing to collaborative team environments.

• Ability to remain calm and professional in fast-paced analytical environments.

Minimum Job Qualifications

• Bachelor’s degree in mathematics, statistics, actuarial science, data science, economics, or a 

   related quantitative field.

• Demonstrated programming experience in R or Python building predictive models, 

   statistical analysis, or econometric modeling.

• 3–6 years of experience in quantitative analysis, statistical modeling, data science, or 

   actuarial analytics.

Preferred Qualifications

• Master’s or PhD in statistics, data science, mathematics, econometrics, or actuarial 

  science.

• Experience in insurance pricing, actuarial analytics, or risk modeling.

• Experience with machine learning frameworks or advanced statistical modeling tools.

• Experience analyzing geo-temporal or spatial datasets.