• Partner directly with CX directors, managers, and executive leadership to deliver prescriptive, data-backed guidance for strategic planning. • Analyze customer health scores, product usage, and support trends to perform deep-dive retrospective analyses on churn and contraction drivers. • Design and execute impact measurement models that move past baseline usage metrics to quantify actual gross retention rate (GRR) improvements, net revenue retention (NRR) gains, and process efficiencies. • Lead the quantitative analysis for complex special projects, including annual account carves, territory balancing, and customer segmentation strategies. • Using Large Language Models (LLMs) to rapidly prototype scripts, automate ad-hoc reporting requests, and build lightweight data workflows. • Actively leverage the native AI components within Snowflake and our broader business intelligence stack to accelerate context gathering and surface predictive customer trends. • Map out how multi-source data flows between our primary platforms to create a unified, accurate view of the post-sales ecosystem. • Write high-performance, production-grade SQL queries directly within Snowflake to manipulate and model complex datasets. • Serve as part of the core CX liaison to the Enterprise Data & Analytics (ED&A) team, owning downstream data requirements and standardizing metric definitions.

• You will bring statistical rigor to business decisions. • Within the BI team, your mission is to go beyond descriptive analysis by applying statistical and machine learning models to find patterns, validate hypotheses, and generate forecasts that guide real strategies. • Day-to-day, you will model complex problems with Python, work with large volumes of data in ClickHouse and BigQuery, and collaborate with product and operations teams to ensure the models deliver real value. • Conduct statistical analyses to answer business questions: hypothesis testing, correlation analysis, segmentation, and predictive modeling; • Perform exploratory data analysis (EDA) to understand the data before modeling, identifying patterns and inconsistencies; • Write complex SQL queries in ClickHouse and BigQuery to extract and prepare data for analysis and modeling; • Use Python for data manipulation, exploratory analyses, and model prototyping; • Communicate results and insights clearly to business teams—translating statistics into decisions; • Collaborate with the BI team to define metrics, data quality standards, and analytical best practices; • Monitor models in production, tracking performance and proposing continuous improvements;

• Responsible for end-to-end delivery of data management services • Collaborate with internal and external customers • Ensure staff deliver high quality, timely service and meet all regulatory requirements • Hire, manage staff performance, utilization, retention, process improvements • Financial management for assigned projects

Role Description At Liberty, our Personal Lines Property & Specialty Product team partners across the company to design and launch home and specialty insurance solutions — from homeowners (property) and condos to renters and other niche lines (specialty)— that meet evolving customer and agent needs. We focus on preparing and executing program rollouts, delivering on our growth roadmap, and modernizing pricing and the technology that supports the work we do. Organized into five functions—State Management, Development, Delivery, Underwriting Effectiveness, and Specialty—we collaborate closely to meet our goals and help customers feel secure today and confident about tomorrow. We are looking for a motivated, analytically driven professional to join the US Property & Specialty Delivery Monitoring team as a Property & Casualty Pricing Insights Advisor. In this role, you will have a direct opportunity to influence and shape our newest homeowners pricing programs through rigorous evaluation of program performance, clear articulation of risk, and actionable recommendations backed by data and sound business judgment. This is a high-visibility, fast paced role with regular exposure to senior and executive leadership. You Will Be Responsible For: - Monitoring the implementation and performance of new pricing programs at both the state and program level, with a focus on key metrics including conversion rates, average quoted premium, segmentation trends, and profitability indicators. - Applying business acumen to translate complex, ambiguous analysis into clear findings and business impact. - Telling a story with data — informing and influencing stakeholders across Delivery, Risk Analytics, Underwriting, and State Management teams. - Delivering executive-level updates through recurring newsletters, memos, and presentations; synthesizing inputs from multiple teams into a single, cohesive narrative. - Building and maintaining monitoring frameworks, guardrails, and quality control processes that support consistent, repeatable program evaluation. - Supporting prioritization of analytical work based on urgency, materiality, and business impact — distinguishing signals that require action from normal market noise. - Leading development of team processes, tools, and analytical capabilities. Qualifications - Bachelor's degree in business, information management, economics, or other quantitative field. Master’s degree preferred. - Minimum 4 years, typically 6 years or more of relevant work experience. - Knowledgeable in data query languages and tools; proficient in new and emerging technologies; may possess data modeling skills. - Highly developed communication and presentation skills. - In-depth knowledge of data concepts, strategies, and methodologies. - In-depth knowledge of data architectures, solutions and designs; extensive knowledge of business operations, strategies and objectives. - Highly developed negotiation, facilitation and consensus building skills. Requirements - Insurance product or pricing knowledge — familiarity with insurance products and pricing mechanics, rate calibration, segmentation, and the pricing program lifecycle is strongly preferred. - Strong analytical and quantitative skills — ability to work with large, complex datasets to identify trends, draw meaningful conclusions, and support data-driven decision making. - Sound business judgment — ability to prioritize findings by impact, operate confidently with limited or noisy data, and recommend clear next steps under uncertainty. - Technical proficiency — advanced Excel, Power BI, and the ability to query and manipulate data using SQL, Python, and/or Snowflake. - Executive communication skills — proven ability to write clearly and concisely for senior audiences, translating data into decision-ready insights. - Cross-functional effectiveness — track record of driving workstreams forward, building alignment across teams, and influencing without direct authority. - Curiosity and intellectual rigor — a natural problem solver who asks the right questions, challenges assumptions, and digs deeper when results don't add up. Benefits - Comprehensive benefits. - Workplace flexibility. - Professional development opportunities. - Opportunities provided through Employee Resource Groups.