About the Company
Porch Group is a leading provider of vertical software and insurance platforms dedicated to transforming the homeownership experience. Positioned as a strategic partner for homebuyers, Porch offers a broad range of differentiated products and services, with homeowners insurance at the core of its offerings. The company's mission is to help individuals move, maintain, and fully protect their homes through innovative solutions and deep industry relationships.
With a focus on leveraging advanced underwriting techniques and comprehensive risk management, Porch aims to dominate the expanding homeowners insurance market by providing exceptional services, leveraging property data, and adopting emerging technologies. Since its inception, Porch has built strong relationships with approximately 30,000 key industry partners, including home inspectors, mortgage companies, and title agencies, facilitating seamless transactions in the home-buying process. The company went public in 2020, ringing the Nasdaq bell and trading under the ticker symbol PRCH.
As a forward-thinking organization, Porch is committed to building a great company and continues to grow rapidly, driven by innovation and a passion to redefine homeownership support.
About the Role The Staff Data Scientist, Insurance Pricing at Porch Group is a senior-level role responsible for shaping the technical approach to homeowners insurance pricing and risk modeling. As a key contributor, you will own complex modeling projects from business strategy to deployment, influencing underwriting, profitability, and retention strategies. Your expertise will be central to developing GLM-based models for pricing and loss cost estimation, as well as deploying machine learning models such as gradient boosting machines and neural networks to enhance underwriting accuracy and competitive positioning.
You will work closely with cross-functional teams—including actuarial, product, and engineering—to translate property data into actionable insights that provide a strategic advantage. This role involves leading the use of non-traditional data sources, such as aerial imagery and satellite data, to assess localized risk factors. You will also oversee the development and monitoring of predictive models that meet regulatory standards, champion best practices in deployment, and foster a culture of experimentation, including exploring generative AI and large language models for innovative solutions.
The ideal candidate will have a significant impact on the company's pricing strategies, mentoring junior team members, and driving measurable business results.
Qualifications
10+ years of experience in data science, with a focus on insurance pricing or risk modeling
Proven track record of technical leadership in complex projects
Expertise in architecting, validating, and deploying GLM-based pricing models in production environments
Strong proficiency in Python and SQL, with experience in scikit-learn, statsmodels, xgboost, and lightgbm
Experience with experimental design, A/B testing, and causal inference in high-traffic settings
Hands-on experience with cloud platforms such as BigQuery and GCP, including MLOps practices
Proficiency with documentation and project management tools like Confluence and Jira within Agile/Scrum frameworks
Master’s or PhD in Statistics, Mathematics, Computer Science, or related quantitative fields (preferred)
Background in actuarial science or insurance mathematics (preferred)
Experience with customer lifetime value, retention, or conversion modeling (preferred)
Knowledge of geospatial data analysis and spatial data sources (preferred)
Familiarity with generative AI, prompt engineering, and fine-tuning for financial services (preferred)
Understanding of model governance, validation frameworks, and regulatory compliance in insurance (preferred)
Responsibilities
Define and lead the technical vision for insurance pricing and risk modeling, establishing best practices and standards across the data science team
Provide technical oversight, mentorship, and guidance to junior data scientists and team members
Design, develop, and deploy GLM-based models for homeowners insurance pricing, including frequency, severity, and loss costs
Create machine learning models such as GBMs and neural networks to improve underwriting accuracy and profitability
Develop ensemble models to predict insured-level profitability, customer retention, and lifetime value, informing strategic decision-making
Leverage non-traditional data sources like aerial imagery, satellite data, and government records to enhance risk assessment accuracy
Collaborate with product, actuarial, engineering, and business teams to prioritize initiatives and integrate data science solutions into operational workflows
Work with actuarial teams to develop, file, implement, and monitor models in compliance with regulatory standards
Champion deployment best practices, including A/B testing, performance monitoring, and continuous model refinement
Drive innovation by exploring emerging techniques such as generative AI and large language models to identify new competitive opportunities
Benefits
Competitive salary range of $168,800 – $236,300 annually, commensurate with experience
Eligibility for long-term incentive awards based on performance and company guidelines
Comprehensive health benefits including three medical plans, two dental plans, and vision coverage
Voluntary plans such as critical illness, hospital indemnity, and accident insurance
Pre-tax savings options including Health Savings Accounts and Flexible Spending Accounts for healthcare, dependent care, and transportation
Company-paid Basic Life and AD&D insurance, along with Short and Long-Term Disability coverage
Voluntary Life and AD&D plans available for employees and their families
Traditional and Roth 401(k) plans with employer matching contributions
Equal Opportunity
Porch Group is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, or veteran status. We believe in fostering a workplace where everyone feels valued and empowered to contribute their best.