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Role Summary

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HIGHLIGHTS

Associate-level P&C analytics role supporting a Technology Risk brokering team in San Francisco. You’ll build bespoke predictive models, validate insurance data, and act as the primary liaison between account teams and internal analytics partners. The role focuses on technology/technology-related exposures and requires 4–6 years of insurance analytics experience and proficiency in Python, SQL, and Excel.

JOB DESCRIPTION SUMMARY

  • Develop bespoke analytical and predictive models for technology risk exposures
  • Serve as primary liaison between brokering/account teams and analytics partners
  • Ensure data completeness, validation, and standardized data preparation
  • Use Python and SQL for analysis; create visualizations in Tableau or Power BI
  • San Francisco office-first role, suited to candidates with 4–6 years' experience

DOMAIN EXPERTISE

  • Insurance analytics or data analysis
  • Data quality assurance and validation
  • Understanding of insurance loss components and market dynamics

KEY REQUIREMENTS

  • 4–6 years of insurance analytics or data analysis experience
  • Bachelor's degree in Actuarial Science, Analytics, Finance, or related field
  • Proficiency in Python, SQL, and Excel
  • Demonstrated experience with data validation and quality assurance processes
  • Strong knowledge of fundamental insurance concepts and loss components

TECH STACK

  • Excel
  • Tableau
  • Power_BI
  • PowerPoint
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Role Summary

Loading...

HIGHLIGHTS

Associate-level P&C analytics role supporting a Technology Risk brokering team in San Francisco. You’ll build bespoke predictive models, validate insurance data, and act as the primary liaison between account teams and internal analytics partners. The role focuses on technology/technology-related exposures and requires 4–6 years of insurance analytics experience and proficiency in Python, SQL, and Excel.

JOB DESCRIPTION SUMMARY

  • Develop bespoke analytical and predictive models for technology risk exposures
  • Serve as primary liaison between brokering/account teams and analytics partners
  • Ensure data completeness, validation, and standardized data preparation
  • Use Python and SQL for analysis; create visualizations in Tableau or Power BI
  • San Francisco office-first role, suited to candidates with 4–6 years' experience

DOMAIN EXPERTISE

  • Insurance analytics or data analysis
  • Data quality assurance and validation
  • Understanding of insurance loss components and market dynamics

KEY REQUIREMENTS

  • 4–6 years of insurance analytics or data analysis experience
  • Bachelor's degree in Actuarial Science, Analytics, Finance, or related field
  • Proficiency in Python, SQL, and Excel
  • Demonstrated experience with data validation and quality assurance processes
  • Strong knowledge of fundamental insurance concepts and loss components

TECH STACK

  • Excel
  • Tableau
  • Power_BI
  • PowerPoint

Job Overview

Salary
Salary not specified
Years of Experience
4+ Years
Work Type
Permanent
Full Time

Ideal Candidate Profile

An Associate-level P&C analytics professional with 4–6 years' insurance analytics experience in technology or specialty lines, proficient in Python and SQL, and preferably ACAS or working toward it.

Benefits

Annual BonusFlexible Hours
Fresh Role
Premium Window
1d
1 days ago

Strategy: Maximize Application Quality

Applications submitted within 72 hours are 2x more likely to land an interview.

"Recruiters are actively watching. Take time to tailor your keywords."

Job Overview

Salary
Salary not specified
Years of Experience
4+ Years
Work Type
Permanent
Full Time

Ideal Candidate Profile

An Associate-level P&C analytics professional with 4–6 years' insurance analytics experience in technology or specialty lines, proficient in Python and SQL, and preferably ACAS or working toward it.

Benefits

Annual BonusFlexible Hours
Fresh Role
Premium Window
1d
1 days ago

Strategy: Maximize Application Quality

Applications submitted within 72 hours are 2x more likely to land an interview.

"Recruiters are actively watching. Take time to tailor your keywords."

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