Data Analytics Lead

PEAK6•Florida Remote, FL

22h•Hybrid

About The Position

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.

Requirements

Bachelor's degree in Statistics, Mathematics, Computer Science, Economics, Business Analytics, or a related quantitative field.
6+ years of progressive experience in data analytics, business intelligence, or a related role, with at least 2 years in a lead or senior capacity.
Advanced proficiency in SQL; strong working knowledge of Python or R for analytical workflows.
Expertise with BI and visualization tools such as Tableau, Power BI, or Looker.
Proven ability to build and communicate complex analyses to executive and non-technical audiences.
Strong understanding of data modeling, data warehousing concepts, and ETL processes.
Excellent project management and organizational skills; ability to manage multiple priorities in a fast-paced environment.
High emotional intelligence with demonstrated ability to influence without formal authority.

Nice To Haves

Master's degree (MBA, MS in Data Science, Analytics, or related discipline).
Relevant certifications such as Google Data Analytics, Tableau Desktop Specialist, or AWS Certified Data Analytics.
Experience in the insurance, financial services, or healthcare industry.
Prior exposure to agency management systems, policy administration platforms, or insurance data warehouses.
Experience working in an Agile/Scrum environment and managing analytics delivery within sprint cycles.
Knowledge of insurance products, terminology, and regulatory environment is a strong plus.

Responsibilities

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.
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 knowledge transfer.
Evaluate and implement new analytics tools and technologies to improve team efficiency and capability.
Partner with business leaders in Sales, Underwriting, Operations, and Finance to translate needs into analytical project plans.
Facilitate requirements-gathering sessions and proactively manage expectations around timelines, scope, and deliverables.
Present analytical findings and recommendations to senior leadership; clearly articulate business impact and suggested actions.
Serve as a subject matter expert for data governance, data definitions, and analytical best practices across the organization.
Collaborate with IT and data engineering on infrastructure priorities, ensuring analytics requirements are represented in the roadmap.
Provide guidance, code review, and technical mentorship to junior and mid-level analysts on the team.
Lead project planning and workload prioritization for analytics initiatives; coordinate cross-functional delivery timelines.
Champion a culture of data-driven decision-making and analytical rigor across the organization.
Contribute to hiring, onboarding, and professional development efforts within the analytics function.