Data Analytics Lead

Company Overview

FOCUS provides cloud-based, core administration solutions (FOCUS Tech) and services (FOCUS Insurance Services) for P&C insurance companies and MGAs. Using decades of industry experience, FOCUS is taking the risk out of insurtech for small, mid-size, and growth-focused insurance organizations.

When you join FOCUS, you immediately become one of our most valued components – and we’re committed to investing in you. That means you can look beyond the paycheck and excellent benefits to an environment that will help you grow and achieve your professional goals through development and advancement opportunities and the support of our outstanding leaders and teammates.

The Lead, Data Analytics plays a critical role within FOCUS' Group's Data & Technology division, driving the strategic use of data to inform business decisions, improve operational efficiency, and enhance client outcomes. This senior individual contributor leads complex analytics initiatives, serves as a subject matter expert across data domains, and acts as a key liaison between data engineering, business stakeholders, and executive leadership.

The ideal candidate is an analytically rigorous, business-savvy professional with deep expertise in insurance or financial services data environments. They excel at translating ambiguous business questions into structured analytical frameworks, mentoring junior analysts, and delivering actionable insights at scale. This role is suited for someone who thrives in a fast-paced, collaborative environment and is passionate about harnessing data to drive meaningful outcomes.

Position Summary

Analytics Strategy & Insight Generation 30%

• Design and lead end-to-end analytics projects addressing strategic business questions across underwriting, claims, distribution, and client experience.
• Develop advanced statistical models, segmentation analyses, and predictive frameworks to surface trends from large, complex datasets.
• Define and track key performance indicators (KPIs) and metrics that drive business accountability and operational improvement.
• Identify data gaps and quality issues; partner with data engineering to resolve root causes and improve data integrity.
• Synthesize findings into clear, compelling narratives for both technical and non-technical audiences.

Data Modeling, Reporting & Visualization 30%

• Architect and maintain scalable data models and pipelines in collaboration with data engineering teams.
• Build and own executive-level dashboards and self-service reporting tools using BI platforms (e.g., Tableau, Power BI, Looker).
• Write complex SQL queries and leverage Python/R for statistical analyses, automation, and ad hoc investigations.
• Document data definitions, methodology, and analytical logic to ensure reproducibility and organizational kn