[Hiring] Insurance Data Analyst @Porch Group

Role Description

The future is bright for the Porch Group, and we'd love for you to be a part of it as our Insurance Data Analyst. In this role, you will partner directly with Product Managers and business leaders across Porch's insurance platform to transform complex insurance data into actionable insights that drive profitable growth. You will support critical decisions across pricing, underwriting, retention, and competitive intelligence, areas that sit at the very core of how Porch wins in the homeowners insurance market.

Your work will span BigQuery, SQL Server, and Power BI, building the analytical infrastructure and dashboards that keep key stakeholders informed and ahead of the curve. If you thrive on solving ambiguous problems autonomously, communicating findings with clarity, and making a measurable impact on a fast-growing insurance business, this is the role for you.

What You Will Do As An Insurance Data Analyst

• Write and maintain SQL queries across BigQuery and SQL Server to support recurring analysis and ad hoc business requests.
• Build and maintain Power BI dashboards tracking key insurance KPIs including quotes, binds, retention, premium, and business mix.
• Perform descriptive and diagnostic analyses to identify trends, drivers, and anomalies across the insurance portfolio.
• Support measurement of product changes using cohorts, pre/post analysis, and trend analysis to quantify business impact.
• Assist with competitive intelligence by gathering, organizing, and summarizing competitor data to inform pricing and product strategy.
• Ensure data accuracy and integrity through QA checks, reconciliations, and thorough documentation of methodology and sources.
• Work autonomously on complex, cross-functional issues with mid-term (12+ month) implications, proactively identifying problems and opportunities.

Qualifications

• Bachelor's degree in Business, Finance, Economics, Statistics, Actuarial Science, or a related field.
• 3+ years of professional experience, including 1+ years in personal lines insurance in data analysis, actuarial, product analytics, or related roles.
• Strong SQL skills with hands-on experience in BigQuery and/or SQL Server.
• Advanced experience building and maintaining dashboards and reports in Power BI.
• Exceptional Microsoft Office skills, especially Excel, with strong attention to detail.
• Demonstrated ability to work on complex issues with mid-term or broader cross-functional implications, exercising wide latitude in determining objectives and approaches.
• Self-starter with a track record of working autonomously and proactively identifying problems before they escalate.
• Proficiency in Python or R for analysis or automation.
• Familiarity using AI tools to accelerate research and analysis.
• Experience working with global and/or US based business teams.
• Excellent written and communication skills in English language.

Requirements

• Working Hours: 8 Hours (Excluding breaks) 4 Core US Hours Overlap (7:30pm - 11:30pm IST) 4 flexible hours (IST).
• Workspace: A quiet space to work, an internet connection of at least 30 Mbps download | 10 Mbps upload.

Benefits

• Pay Range*: 693,800 - 971,300 INR annually.
• Comprehensive coverage for your health, life, and financial well-being.
• Medical insurance, accident insurance, and retiral benefits.
• Wellness programs including 12 company-paid holidays, 2 flexible holidays, privilege/earned leave, casual/sick leave, paid maternity and paternity leaves, and weekly wellness events.

Company Description

Porch Group is a leading vertical software and insurance platform and is positioned to be the best partner to help homebuyers move, maintain, and fully protect their homes. We offer differentiated products and services, with homeowners insurance at the center of this relationship.

• Providing the best services for homebuyers.
• Led by advantaged underwriting in insurance.
• To protect the whole home.
• Built deep relationships with approximately 30 thousand companies key to the home-buying transaction.