The Product Delivery Monitoring Team is looking for a Consultant to help advance the next generation of Personal Lines Auto monitoring capabilities. This highly visible individual contributor role will partner across the organization to strengthen how we monitor Auto pricing programs, detect emerging issues, improve data accuracy, and scale sustainable monitoring practices across the broader Auto portfolio.

This role will focus heavily on building strategic monitoring capabilities that reduce programmatic risk, improve early issue detection, and create a scalable foundation for future growth. In addition, this individual will support core Auto Program Monitoring responsibilities, with a focus on program-level monitoring and analysis of recently launched pricing programs.

The ideal candidate is highly analytical and technically capable, comfortable working independently, able to navigate ambiguity, and effective at partnering cross-functionally with both technical and business audiences.

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.

Ideal candidate will have : 

• 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 with Python and GitHub preferred.

• 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

• Familiarity with insurance rating programs, pricing implementations, or post-launch program evaluation preferred.

Preferred Qualifications

• Experience with Python and GitHub preferred.

• 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. 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.