Data Analytics Lead (Property & Casualty)

WHO WE ARE We are PEAK6, a leading investment firm, using technology to find a better way of doing things. The company’s first tech-based solution was developed in 1997 to optimize options trading, and over the past two decades, the same formula has been used across a range of industries, asset classes, and business stages to consistently deliver superior results. Today, PEAK6 seeks transformational opportunities to provide capital and strategic support to entrepreneurs and forward-thinking businesses. PEAK6’s core brands include PEAK6 Capital Management, PEAK6 Strategic Capital, Apex Fintech Solutions, FOCUS, We Insure, Evil Geniuses, Poker Power, Zogo, and Bruce Markets. ABOUT THIS ROLE 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 Property and Casualty(P&C) i nsurance 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 P&C 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 knowledge transfer. Evaluate and implement new analytics tools and technologies to improve team efficiency and capability. Stakeholder Collaboration & Business Partnership 25% Partner with business leaders in Sales, P&C 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. Team Leadership & Mentorship 15% 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. Education Required: Bachelor's degree in Statistics, Mathematics, Computer Science, Economics, Business Analytics, or a related quantitative field. Preferred: Master's degree (MBA, MS in Data Science, Analytics, or related discipline). Preferred: Relevant certifications such as Google Data Analytics, Tableau Desktop Specialist, or AWS Certified Data Analytics. Work Experience Required: 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. Preferred: Experience in the insurance, financial services, or healthcare industry. Preferred: Prior exposure to agency management systems, policy administration platforms, or insurance data warehouses. Preferred: Experience working in an Agile/Scrum environment and managing analytics delivery within sprint cycles. Knowledge, Skills & Abilities 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. Knowledge of insurance products, terminology, and regulatory environment is a strong plus. Supervisory Responsibility This role does not carry formal supervisory responsibility. However, the Lead, Data Analytics is expected to provide informal mentorship, technical guidance, and project leadership to junior and mid-level analysts within the team. Working Conditions Tr