Data Analyst, Analytics & AI Insights

Everest•Warren Township, NJ

1d•$77,000 - $105,000•Hybrid

About The Position

Everest Insurance, a member of Everest Re Group Ltd., is seeking a Data Analyst with 1–3 years of relevant experience within the P&C insurance industry. This role is ideal for someone with strong data mining and analytical skills, who is eager to contribute in a fast-paced, collaborative environment. This hybrid role requires 3 days onsite in Warren, NJ. The Data Analyst will partner with business stakeholders and IT teams to support reporting, analytics, and AI-driven insights. The role focuses on analyzing data, building dashboards, and leveraging modern tools (including Gen-AI & Co-Pilot) to enhance decision-making and operational efficiency.

Requirements

Bachelor’s degree in Statistics, Mathematics, Computer Science, MIS, or a related field.
1–3 years of experience in data analytics, reporting, or business intelligence within the Property & Casualty (P&C) insurance industry.
Ability to learn new tools and technologies quickly.
Working knowledge of SQL and/or Excel for data analysis and reporting.
Familiarity with data structures and basic data modeling concepts.
Basic understanding of scripting tools such as Python or R.
Ability to interpret data and communicate insights clearly.
Strong attention to detail and data accuracy.
Good communication and collaboration skills.

Nice To Haves

Exposure to applying Gen-AI and LLM concepts to business analytics is a plus.
Curiosity and interest in applying AI/automation to solve business problems.
Strong organizational skills and ability to manage multiple priorities.
Collaborative mindset with the ability to work across business and IT teams.
Comfort working in a fast-paced, agile environment.

Responsibilities

Develop and maintain enterprise level reporting and analytical applications using emerging technology, and able to handle high volume data and complex calculations.
Extract, clean, and transform data from multiple sources using SQL, Excel, or other tools.
Leverage AI-enabled tools (e.g., Power BI Copilot, Python-based libraries, or LLM tools) to enhance data analysis, automate insights, and improve reporting efficiency.
Perform data analysis to identify trends, patterns, and insights across underwriting and business performance metrics.
Ensure data quality and accuracy through validation and reconciliation of datasets.
Support recurring reporting and ad hoc analytical requests from business stakeholders.
Assist in the development of data models and reporting structures
Collaborate with IT and data teams to understand data sources and improve reporting solutions.
Document data definitions, report logic, and key metrics to support consistency and transparency.
Translate analytical findings into clear visualizations and business-friendly insights.