Statistical Researcher

{
  "content_hash": "a63947f680c46c88aaa89883b682515024359e08d4f8fe8f9d47bb9b3ef0e668",
  "source_hash": "349486c3f9d1f4a8bb2494b87de7ee092c07b7eb3c4fa5a89be1ce6109710fd8",
  "last_changed_at": "2026-06-06T11:42:22.375Z",
  "active_status": "active"
}

{
  "language": "en",
  "location": {
    "raw": "Boston, MA, United States",
    "city": "Boston",
    "region": "MA",
    "country": "United States",
    "is_remote": false,
    "confidence": 0.8
  },
  "salary_max": null,
  "salary_min": null,
  "inferred_at": "2026-06-06T11:42:22.215Z",
  "launch_scope": {
    "reason": "english_us_canada",
    "included": true,
    "language": "en",
    "location": {
      "raw": "Boston, MA, United States",
      "city": "Boston",
      "region": "MA",
      "country": "United States",
      "is_remote": false,
      "confidence": 0.8
    },
    "countries": [
      "United States"
    ]
  },
  "remote_policy": "hybrid",
  "salary_period": "day",
  "workplace_type": "hybrid",
  "salary_currency": null
}

{}

{
  "detail": {
    "Id": "3668",
    "Title": "Statistical Researcher",
    "media": [],
    "skills": [],
    "JobType": null,
    "Category": "Data Science and Business Intelligence",
    "JobGrade": null,
    "JobLevel": null,
    "JobShift": null,
    "WorkDays": null,
    "WorkHours": null,
    "WorkYears": null,
    "Department": null,
    "HotJobFlag": false,
    "StudyLevel": "Master's Degree",
    "WorkMonths": null,
    "WorkerType": null,
    "GeographyId": 300000007117258,
    "JobFamilyId": 300000007039350,
    "JobFunction": "Engineering/Technical/Scientif",
    "JobSchedule": "Full time",
    "BusinessUnit": null,
    "ContractType": null,
    "Organization": null,
    "TrendingFlag": false,
    "workLocation": [
      {
        "Country": "US",
        "Region1": "Suffolk",
        "Region2": "MA",
        "Region3": null,
        "Building": null,
        "Latitude": "42.35059",
        "Longitude": "-71.06044",
        "LocationId": 300000011156952,
        "PostalCode": "02111",
        "TownOrCity": "Boston",
        "AddressLine1": "Lafayette City Center",
        "AddressLine2": "2 Avenue de Lafayette",
        "AddressLine3": "Floor 2",
        "AddressLine4": null,
        "LocationName": "Boston-Lafayette"
      }
    ],
    "ContentLocale": "en",
    "HiringManager": null,
    "LegalEmployer": null,
    "RequisitionId": 300000412421528,
    "WorkplaceType": "Hybrid",
    "BusinessUnitId": 300000007066271,
    "OrganizationId": 1,
    "GeographyNodeId": 100001459580702,
    "JobFunctionCode": "VK_ENG",
    "LegalEmployerId": 300000007041255,
    "PrimaryLocation": "Boston, MA, United States",
    "RequisitionType": "Experienced",
    "NumberOfOpenings": null,
    "WorkplaceTypeCode": "ORA_HYBRID",
    "BeFirstToApplyFlag": false,
    "otherWorkLocations": [],
    "secondaryLocations": [],
    "ExternalContactName": null,
    "ShortDescriptionStr": "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.",
    "ExternalContactEmail": null,
    "ExternalPostedEndDate": null,
    "OtherRequisitionTitle": null,
    "requisitionFlexFields": [],
    "ApplyWhenNotPostedFlag": false,
    "DomesticTravelRequired": null,
    "ExternalDescriptionStr": "<div style=\"font-family: &quot;Segoe UI&quot;; font-size: 14px; font-style: normal; font-weight: 400; line-height: 20px;\"><p>Join Verisk’s <strong>Extreme Event Solutions</strong> and become part of a growing <strong>Research and Modeling Department</strong> that sits at the intersection of statistics, data, and real‑world catastrophe risk. As a <strong>Statistical Researcher</strong>, you’ll work on the <strong>Financial and Uncertainty Modeling team</strong> in Boston, collaborating closely with statisticians, mathematicians, analysts, and geoscientists to help quantify the financial impact of extreme events around the world.</p><p>This role is ideal for someone with a strong quantitative foundation and a genuine desire to <strong>learn and grow</strong>. 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.</p></div>",
    "ObjectVerNumberProfile": null,
    "PrimaryLocationCountry": "US",
    "CorporateDescriptionStr": "<p></p>\n<p>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.</p>\n<p>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.&nbsp;</p>\n<p>For the eighth consecutive year, Verisk is proudly recognized as a Great Place to Work® for outstanding workplace culture in the US, the fourth consecutive year in the UK, Spain, and India, and the second consecutive year in Poland. In addition, 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, testaments to the value we place on workplace culture.</p>\n<p>We’re 7,000 people strong.&nbsp; 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.</p>\n<p>&nbsp;<b>Verisk Businesses</b></p>\n<p><a href=\"https://www.verisk.com/insurance/capabilities/underwriting/\" target=\"_blank\" style=\"margin-top:0px; margin-bottom:0px\" rel=\"nofollow\">Underwriting Solutions</a>&nbsp;— provides underwriting and rating solutions for auto and property, general liability, and excess and surplus to assess and price risk with speed and precision</p>\n<p><a href=\"https://www.verisk.com/insurance/capabilities/claims/\" target=\"_blank\" style=\"margin-top:0px; margin-bottom:0px\" rel=\"nofollow\">Claims Solutions</a>&nbsp;— supports end-to-end claims handling with analytic and automation tools that streamline workflow, improve claims management, and support better customer experiences</p>\n<p><a href=\"https://www.verisk.com/property-estimating-solutions/\" target=\"_blank\" style=\"margin-top:0px; margin-bottom:0px\" rel=\"nofollow\">Property Estimating Solutions</a>&nbsp;— 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</p>\n<p><a href=\"https://www.verisksequel.com/\" target=\"_blank\" rel=\"nofollow\">Specialty Business Solutions</a>&nbsp;— 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</p>\n<p><a href=\"https://www.verisk.com/solutions/catastrophe-risk-solutions/\" target=\"_blank\" rel=\"nofollow\">Catastrophe and Risk Solutions</a>&nbsp;— provides risk modeling solutions to help individuals, businesses, and society become more resilient to catastrophic events.</p>\n<p><a href=\"https://www.verisk.com/verisk-marketing-solutions/\" target=\"_blank\" style=\"margin-top:0px; margin-bottom:0px\" rel=\"nofollow\">Marketing Solutions</a>&nbsp;— delivers data and insights to improve the reach, timing,relevance, and compliance of every consumer engagement</p>\n<p><a href=\"https://www.verisk.com/insurance/life-insurance/\" target=\"_blank\" style=\"margin-top:0px; margin-bottom:0px\" rel=\"nofollow\">Life Insurance Solutions</a>&nbsp;– 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.</p>\n<p><a href=\"https://www.maplecroft.com/\" target=\"_blank\" style=\"margin-top:0px; margin-bottom:0px\" rel=\"nofollow\">Verisk Maplecroft</a>&nbsp;— provides intelligence on sustainability, resilience, and ESG, helping people, business, and societies become stronger</p>\n<p>Verisk Analytics is an equal opportunity employer.</p>\n<p>Verisk invests in a benefits package for all employees that includes the following: Health Insurance, a Retirement Plan, Disability benefits, and a Paid Time Off program. We offer a competitive total rewards package that includes base salary determined based on role, experience, skill set, and location.</p>\n<p>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. Verisk’s minimum hiring age is 18 except in countries with a higher age limit subject to applicable law.</p>\n<p><a href=\"https://www.verisk.com/company/careers/\" target=\"_blank\" rel=\"nofollow\">https://www.verisk.com/company/careers/</a></p>\n<p>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.</p>\n<p><a href=\"https://www.verisk.com/49041b/siteassets/media/downloads/verisk-global-employee-privacy-notice.pdf\" target=\"_blank\" rel=\"nofollow\">Verisk Employee Privacy Notice</a></p>",
    "ExternalPostedStartDate": "2026-06-02T13:26:23+00:00",
    "ExternalQualificationsStr": "<div style=\"font-family: &quot;Segoe UI&quot;; font-size: 14px; font-style: normal; font-weight: 400; line-height: 20px;\"><p><strong>Required qualifications:</strong></p><ul><li><strong>Graduate degree</strong> in a quantitative field such as statistics, mathematics, data science, or a related discipline</li><li><strong>2–5 years of professional experience</strong> working on data analytics or quantitative projects</li><li>Strong analytical and quantitative skills with a solid understanding of <strong>probability concepts</strong></li><li>Basic programming proficiency; experience with <strong>R or similar statistical programming languages</strong> preferred</li><li>Excellent written and verbal communication skills, with the ability to present technical work clearly</li><li>Strong time‑management, organizational, and problem‑solving skills</li></ul><p><strong>Nice to have:</strong></p><ul><li>Experience working with <strong>insurance claims data</strong>, insurance policy conditions, or actuarial concepts</li><li>Exposure to <strong>spatial statistics</strong> or catastrophe‑related modeling</li><li>Familiarity with <strong>C++</strong></li><li>Knowledge or exposure to <strong>large language models (LLMs)</strong></li></ul><p><strong>#LI-BH1</strong></p></div>",
    "InternalQualificationsStr": "<div style=\"font-family: &quot;Segoe UI&quot;; font-size: 14px; font-style: normal; font-weight: 400; line-height: 20px;\"><p><strong>Required qualifications:</strong></p><ul><li><strong>Graduate degree</strong> in a quantitative field such as statistics, mathematics, data science, or a related discipline</li><li><strong>2–5 years of professional experience</strong> working on data analytics or quantitative projects</li><li>Strong analytical and quantitative skills with a solid understanding of <strong>probability concepts</strong></li><li>Basic programming proficiency; experience with <strong>R or similar statistical programming languages</strong> preferred</li><li>Excellent written and verbal communication skills, with the ability to present technical work clearly</li><li>Strong time‑management, organizational, and problem‑solving skills</li></ul><p><strong>Nice to have:</strong></p><ul><li>Experience working with <strong>insurance claims data</strong>, insurance policy conditions, or actuarial concepts</li><li>Exposure to <strong>spatial statistics</strong> or catastrophe‑related modeling</li><li>Familiarity with <strong>C++</strong></li><li>Knowledge or exposure to <strong>large language models (LLMs)</strong></li></ul><p><strong>#LI-BH1</strong></p></div>",
    "OrganizationDescriptionStr": "",
    "primaryLocationCoordinates": [
      {
        "Latitude": "42.35866",
        "Longitude": "-71.05674",
        "CountryCode": "US",
        "GeographyId": 300000007117258,
        "GeographyNodeId": 100001459580702
      }
    ],
    "ExternalResponsibilitiesStr": "<div style=\"font-family: &quot;Segoe UI&quot;; font-size: 14px; font-style: normal; font-weight: 400; line-height: 20px;\"><p>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:</p><ul><li>Analyze <strong>insurance claims data</strong> from catastrophic events such as hurricanes, earthquakes, floods, and severe thunderstorms</li><li>Test and validate new modeling methodologies by writing code (primarily in <strong>R or C++</strong>) and running simulations</li><li>Assess the accuracy and behavior of statistical approaches using data‑driven analysis</li><li>Document methodologies, assumptions, and results clearly and thoroughly</li><li>Create concise summaries, visualizations, and presentations to communicate findings</li><li>Partner with <strong>Client Services</strong> to help explain methodologies and support responses to client questions</li></ul></div>",
    "InternalResponsibilitiesStr": "<div style=\"font-family: &quot;Segoe UI&quot;; font-size: 14px; font-style: normal; font-weight: 400; line-height: 20px;\"><p>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:</p><ul><li>Analyze <strong>insurance claims data</strong> from catastrophic events such as hurricanes, earthquakes, floods, and severe thunderstorms</li><li>Test and validate new modeling methodologies by writing code (primarily in <strong>R or C++</strong>) and running simulations</li><li>Assess the accuracy and behavior of statistical approaches using data‑driven analysis</li><li>Document methodologies, assumptions, and results clearly and thoroughly</li><li>Create concise summaries, visualizations, and presentations to communicate findings</li><li>Partner with <strong>Client Services</strong> to help explain methodologies and support responses to client questions</li></ul></div>",
    "InternationalTravelRequired": null
  },
  "list_job": {
    "Id": "3668",
    "Title": "Statistical Researcher",
    "JobType": null,
    "Distance": 1780358400000,
    "JobShift": null,
    "Language": "US",
    "WorkDays": null,
    "JobFamily": null,
    "Relevancy": 7,
    "WorkHours": null,
    "Department": null,
    "HotJobFlag": false,
    "PostedDate": "2026-06-02",
    "StudyLevel": null,
    "WorkerType": null,
    "GeographyId": 300000007117258,
    "JobFunction": null,
    "JobSchedule": null,
    "BusinessUnit": null,
    "ContractType": null,
    "ManagerLevel": null,
    "Organization": null,
    "TrendingFlag": false,
    "workLocation": [
      {
        "Country": "US",
        "Region1": "Suffolk",
        "Region2": "MA",
        "Region3": null,
        "Building": null,
        "Latitude": 42.35059,
        "Longitude": -71.06044,
        "LocationId": 300000011156952,
        "PostalCode": "02111",
        "TownOrCity": "Boston",
        "AddressLine1": "Lafayette City Center",
        "AddressLine2": "2 Avenue de Lafayette",
        "AddressLine3": "Floor 2",
        "AddressLine4": null,
        "LocationName": "Boston-Lafayette"
      }
    ],
    "LegalEmployer": null,
    "MediaThumbURL": null,
    "WorkplaceType": "Hybrid",
    "BusinessUnitId": 300000007066271,
    "OrganizationId": 1,
    "PostingEndDate": null,
    "LegalEmployerId": 300000007041255,
    "PrimaryLocation": "Boston, MA, United States",
    "WorkDurationYears": null,
    "WorkplaceTypeCode": "ORA_HYBRID",
    "BeFirstToApplyFlag": false,
    "WorkDurationMonths": null,
    "otherWorkLocations": [],
    "secondaryLocations": [],
    "ShortDescriptionStr": "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.",
    "requisitionFlexFields": [],
    "DomesticTravelRequired": null,
    "PrimaryLocationCountry": "US",
    "ExternalQualificationsStr": null,
    "ExternalResponsibilitiesStr": null,
    "InternationalTravelRequired": null
  },
  "detail_meta": {
    "url": "https://fa-ewmy-saasfaprod1.fa.ocs.oraclecloud.com/hcmRestApi/resources/latest/recruitingCEJobRequisitionDetails?expand=all&onlyData=true&finder=ById;Id=%223668%22,siteNumber=cx_1",
    "http_status": 200,
    "content_type": "application/json",
    "response_bytes": 14717
  },
  "detail_errors": []
}