Statistical Researcher
hackajob, Boston, MA, United States
hackajob 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
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)
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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
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)
#J-18808-Ljbffr