Statistical Researcher

Archer; Boston (MA); In loco; USD 90.000 - 130.000; Tempo pieno

Descrizione del lavoro

Verisk’s Extreme Event Solutions is seeking a Statistical Researcher in Boston to join the Financial and Uncertainty Modeling team. You will work with statisticians, mathematicians, analysts, and geoscientists to quantify the financial impact of extreme events worldwide.

The role emphasizes strong quantitative skills, learning and growth, and translating complex findings into clear insights for internal partners and client-facing teams.

Competenze

• Graduate degree in a quantitative field such as statistics, mathematics, data science, or a related discipline.
• 2–5 years of professional experience in data analytics or quantitative projects.
• Strong analytical and quantitative skills with a solid understanding of probability concepts.
• Basic programming proficiency with R or other statistical languages.

Mansioni

• Analyze insurance claims data from catastrophic events.
• Test and validate new modeling methodologies by coding in R or C++ and running simulations.
• Assess the accuracy of statistical approaches using data-driven analysis.
• Document methodologies, assumptions, and results clearly.
• Create concise summaries, visualizations, and client-ready presentations.
• Collaborate with Client Services to explain methodologies and respond to questions.

Conoscenze

Analytical skills

Quantitative skills

Probability concepts

R programming

Communication skills

Time management

Problem solving

Formazione

Graduate degree in statistics, mathematics, data science, or related discipline

Strumenti

R

C++

Descrizione del lavoro

Archer is collaborating with Verisk to connect them with exceptional professionals for this role.

Description

Join Verisk’s Extreme Event Solutions and become part of a growing Research and Modeling Department that sits at the intersection of statistics, data, and real‑world catastrophe risk. As a Statistical Researcher, you’ll work on the Financial and Uncertainty Modeling team in Boston, collaborating closely with statisticians, mathematicians, analysts, and geoscientists to help quantify the financial impact of extreme events around the world.

This role is ideal for someone with a strong quantitative foundation and a genuine desire to learn and grow. You’ll develop deep expertise across a broad set of topics, including catastrophic events and modeled perils, global postal code systems, insurance and policy terms, and probability distributions—while applying those concepts to real insurance claims data. Strong communication skills are key, as you’ll translate technical findings into clear insights for both internal partners and client‑facing teams.

Responsibilities

In this role, you’ll apply your analytical and technical skills to support the development and validation of financial and uncertainty models tied to catastrophic risk. Key responsibilities include:

• Analyze insurance claims data from catastrophic events such as hurricanes, earthquakes, floods, and severe thunderstorms
• Test and validate new modeling methodologies by writing code (primarily in R or C++) and running simulations
• Assess the accuracy and behavior of statistical approaches using data‑driven analysis
• Document methodologies, assumptions, and results clearly and thoroughly
• Create concise summaries, visualizations, and presentations to communicate findings
• Partner with Client Services to help explain methodologies and support responses to client questions

Qualifications

Required qualifications:

• Graduate degree in a quantitative field such as statistics, mathematics, data science, or a related discipline
• 2–5 years of professional experience working on data analytics or quantitative projects
• Strong analytical and quantitative skills with a solid understanding of probability concepts
• Basic programming proficiency; experience with R or similar statistical programming languages preferred
• Excellent written and verbal communication skills, with the ability to present technical work clearly
• Strong time‑management, organizational, and problem‑solving skills

Nice To Have

• Experience working with insurance claims data, insurance policy conditions, or actuarial concepts
• Exposure to spatial statistics or catastrophe‑related modeling
• Familiarity with C++
• Knowledge or exposure to large language models (LLMs)