Analytics Lead

AmTrust Financial Services, Inc.•Jersey City, NJ

1d•Hybrid

About The Position

The Analytics Lead will play a critical role in driving data-informed decision making across AmTrust Financial. This individual will lead advanced analytics initiatives, partner with business and technology stakeholders, and develop scalable analytical solutions that improve operational efficiency, underwriting performance, risk management, and customer outcomes.

Requirements

Bachelor's degree in Analytics, Data Science, Statistics, Mathematics, Computer Science, Finance, or a related field.
6+ years of experience in analytics, business intelligence, or data science roles.
Strong proficiency in SQL and experience with BI tools such as Power BI, Tableau, or similar platforms.
Proven ability to use data to identify business opportunities, solve complex operational challenges, and influence company strategy.
Exceptional communication skills. "Tell a story" with data, making complex insights easy for non-technical stakeholders to understand.
Experience managing the full lifecycle of analytics initiatives, from initial discovery to final delivery and measurement of business impact.
A deep understanding of business drivers and how to track them via KPIs.

Nice To Haves

Experience in insurance, financial services, or a highly regulated industry.
Advanced degree in Data Science, Analytics, MBA, or related field.
Familiarity with cloud platforms such as Azure or AWS.
Experience with predictive modeling, machine learning, or statistical analysis tools (Python, R, SAS).
Strong change management and stakeholder engagement skills.

Responsibilities

Design, develop, and oversee dashboards, KPIs, and reports that provide actionable insights to leadership.
Partner with departments like underwriting, Finance, or Operations to build a unified, data-driven culture.
Drive advanced analytics initiatives including predictive modeling, segmentation, trend analysis, and automation.
Ensure data accuracy, governance, and adherence to regulatory and compliance requirements.
Support enterprise-wide data initiatives including cloud analytics platforms, data warehouses, and self-service BI tools.
Establish best practices for analytics development, documentation, and quality assurance.