Develop a deep understanding of underwriting workflows, operational processes, and financial levers within your assigned GS segment.
Analyze key KPIs and performance trends, identifying meaningful shifts and diagnosing underlying causes.
Support routine monthly portfolio reviews across GS lines, including analysis of flow, KPIs, claims trends, underwriting behaviors, and insights from partner tools.
Create and enhance performance metrics and KPI frameworks, ensuring clarity, consistency, and alignment with business needs.
Partner with and support Business Intelligence professionals to enable clear, durable, and self-serve dashboards for business partners.
Partner with and support Data Science professionals to help measure the success of their solutions.
Develop an understanding of Data Science solutions and other technologies that support and transform GS Underwriting.
Partner with and support Data Engineering professionals to ensure data quality and shared understanding of data assets.
Partner with and support Asset Owner professionals to ensure clear, accurate communication with stakeholders and proper documentation of work-effort prioritization and requirements.
Independently source, transform, and validate data using SQL; maintain proactive communication with engineering partners on data quality and structure.
Build automated, repeatable analytical workflows using tools such as Python, Power BI, and Tableau.
Conduct statistical analyses (e.g., correlation and trend modeling) to identify meaningful patterns and insights.
Synthesize analytical findings into concise, clear narratives for GS Underwriting leadership and partner teams.
Present insights and recommendations through polished PowerPoint materials tailored to varying technical and leadership levels.
Collaborate with Underwriting and cross-functional teams to identify improvement opportunities and support execution of business strategies.
Combine and reconcile data from multiple sources, developing a strong understanding of GS data assets, lineage, and quality considerations.
Build trusted working relationships with Underwriting, Product, Actuarial, Claims, and Finance through reliable analysis, open communication, and consistent delivery.
Respond to ad-hoc analytical requests, providing clarity on definitions, methods, and drivers; offer guidance on KPI interpretation and visualization best practices.
Maintain strong, clear documentation of work-effort progress and analysis activities.
Adhere to and promote strong agile practices.

Requirements

2+ years of SQL project work
1+ years of hands on work with Python for analytical and automation tasks
2+ years' experience with Power BI / Tableau or other visualization software
Strong written and verbal communication skills
Curiosity, creativity, and comfort navigating ambiguity
Strong Excel skills
Understanding of insurance performance concepts (rate, retention, loss trends)
Self-motivated; can work independently and in teams
Openness to learning new tools & domain knowledge
Bachelor’s degree required, preferably in Data Analytics, Statistics, Economics, Mathematics, Business, or a related quantitative field
College-level statistical knowledge
Familiarity with Agile practices (preferred)

Benefits

Competitive salary
Bonuses
Long-term incentives
On-the-spot recognition

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

SQLPythonPower BITableaustatistical analysisExceldata transformationdata validationKPI frameworksautomated analytical workflows

Soft Skills

written communicationverbal communicationcuriositycreativityself-motivatedteam collaborationopenness to learningnavigating ambiguitystrong documentationrelationship building