Principal Analytics Analyst, Data Office

As a Principal Analytics Analyst / Senior Analytics Analyst, you'll be a key contributor on a small, high‑impact team that turns complex legal and regulatory questions into clear analytical requirements and high‑quality, insight-driven deliverables. You'll go beyond producing extracts and reporting to conduct in-depth analysis, with claims data. This is a great role for someone who enjoys a mix of forensic problem solving, stakeholder partnership, and hands-on data analysis, and who takes pride in delivering insights that stand up to scrutiny. This position may have in-office requirements depending on candidate location. Conduct deep-dive analysis of complex claims data to identify trends, anomalies, and key insights that directly inform legal strategy, regulatory responses, and compliance assessments. Partner with Legal & Compliance stakeholders to clarify request intent, scope, timelines, and success criteria. Adapt communication style appropriately to share project results, opportunities, and successes with both technical and business (non-technical) leaders. Develop and deliver claims analytical solutions, including everything from foundational claim-level extracts to statistical summaries, predictive metrics, and interactive dashboards using tools like SQL/Snowflake, SAS Viya, Python, and other BI tools as needed. Prioritize efforts to meet delivery timelines, proactively communicating risks to stakeholders. Apply strong data QA practices (reconciliations, trend analysis, reasonableness checks, peer review) to ensure both the data and the resulting analysis are accurate and defensible. Proactively identify opportunities for analysis; partner with stakeholders to move beyond reactive data pulls to a more forward-looking, analytics-driven approach. Produce and maintain clear documentation (methodology, definitions, assumptions/limitations, data lineage) so deliverables are reproducible and audit-ready. Help improve team efficiency by creating reusable code modules, templates, and standardized “request packages” for recurring stakeholder needs. Collaborate with data product and engineering partners to identify high-value recurring requests that should be supported by curated data assets. Demonstrates an understanding of new technologies as needed to progress initiatives, including leveraging approved AI tools to improve processes (within guardrails). Participate in the team's operating cadence (standups, intake/triage, prioritization) and proactively communicate status, risks, and blockers. Acts as a technical guide and mentor for lower level associates. Embrace Diversity, Equity and Inclusion culture creating long-lasting and trusting relationships with teammates. Deliverables are accurate, consistent, and well-documented, with fewer last-minute surprises or rework cycles. 3-5+ years of professional experience in data analytics, with a strong preference for experience in the property and casualty insurance industry. Strong working knowledge of SQL and experience working with large datasets (Snowflake or similar platforms preferred). Proven experience in claims analytics, with a strong understanding of claims data concepts (e.g., claim/exposure/transaction grain, paid/incurred/reserve, claim lifecycle) and familiarity with claims systems (e.g., Guidewire, Claims WorkBench). Experience building data deliverables end-to-end: requirements → analysis & insight generation → QA → stakeholder delivery. Strong communication skills; comfortable translating complex analytical findings into clear, concise narratives for non-technical audiences. Experience supporting Compliance, Regulatory, or Legal stakeholders, or producing audit-ready deliverables. Experience with Power BI or similar BI tools. Experience with Python or SAS for data analysis is a plus. Strong written and oral communication skills required Bachelor`s Degree in Computer Science, Computer Engineering, or related discipline preferred Master`s in same or related disciplines strongly preferred 5-7 years experience in coding for data management, data warehousing, or other data environments, including, but not limited to, SQL, SAS and experience working with large datasets (Snowflake or similar platforms preferred). 5-7 years experience as developer with top quadrant Business Intelligence tools