Note: The job is a remote job and is open to candidates in USA. Liberty Mutual Insurance provides personal lines auto insurance solutions supported by data, analytics, and modern pricing technology. The Consultant will develop and scale monitoring and anomaly detection capabilities, analyze pricing program performance and data quality, automate reporting, and communicate actionable insights across technical and business teams.
Responsibilities
- Drive the development and scaling of continuous monitoring and anomaly detection capabilities to reduce programmatic risk across the Auto portfolio
- Improve data accuracy and early issue detection across rating programs, key business metrics, and Auto program results
- Build scalable monitoring processes, tools, dashboards, and analytical frameworks that support future-state portfolio monitoring and program-level analysis
- Reduce manual effort and response time through automation, improved reporting, and cross-functional coordination
- Support program-level monitoring for Personal Lines Auto pricing programs by analyzing key metrics, identifying emerging trends, and assessing whether results are performing as expected
- Query, manipulate, and analyze large datasets to investigate anomalies, identify root causes, and communicate actionable insights to technical and non-technical audiences
- Partner with teams across USDS, the Data Office, IT, Risk Analytics, Underwriting, State Management, and other business areas to identify issues, coordinate solutions, and improve monitoring effectiveness
- Provide timely updates and recommendations to stakeholders on monitoring results, data quality, program performance, and emerging risks
Skills
- • Strong analytical, problem-solving, and decision-making skills, with the ability to identify patterns, investigate root causes, and develop practical recommendations
- • Proficient in SQL, Power BI, Excel, PowerPoint, and Snowflake
- • Experience building dashboards, reporting tools, analytical frameworks, and repeatable processes
- • Ability to communicate complex analytical findings clearly and effectively to technical and non-technical audiences
- • Strong planning, organizational, analytical, decision-making, and communication skills
- • Prior experience in Personal Lines, auto insurance, pricing, product, or broader insurance analytics
- • Experience with anomaly detection, continuous monitoring, data quality monitoring, automation, or early issue detection
- • Experience partnering with data, technology, underwriting, risk analytics, state management, or product teams
- • Familiarity with insurance rating programs, pricing implementations, or post-launch program evaluation
- ***This role has a hybrid work schedule (2 days onsite) for candidates based in Portsmouth, NH, Boston, MA, Plano, TX, Indianapolis, IN and Columbus, OH. Otherwise, this role is remote***
- * Bachelor's degree in business, information management, economics, or other quantitative field
- * 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
- Experience with Python and GitHub preferred
- • Experience with Python and GitHub preferred
- Master's degree preferred
Benefits
- 20 days of flexible time off annual accrual
- This role has a hybrid work schedule (2 days onsite) for candidates based in Portsmouth, NH, Boston, MA, Plano, TX, Indianapolis, IN and Columbus, OH. Otherwise, this role is remote
- Comprehensive benefits
- Workplace flexibility
- Professional development opportunities
- Opportunities provided through Employee Resource Groups
- Commission and/or bonus earnings may be included in the corresponding compensation plan
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