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. We differentiate and look to win in the massive and growing homeowners insurance opportunity by 1) providing the best services for homebuyers, 2) led by advantaged underwriting in insurance, 3) to protect the whole home.
As a leader in the home services software-as-a-service (“SaaS”) space, we’ve built deep relationships with approximately 30 thousand companies that are key to the home-buying transaction, such as home inspectors, mortgage companies, and title companies.
In 2020, Porch Group rang the Nasdaq bell and began trading under the ticker symbol PRCH. We are looking to build a truly great company and are JUST GETTING STARTED.
Job Title: Senior Data Scientist, Insurance Pricing
Location: United States
Workplace Type: Remote
Job Summary
The future is bright for the Porch Group, and we’d love for you to be a part of it as our Senior Data Scientist, Insurance Pricing.
As a senior member of our data science team, you will own the development and deployment of our homeowners insurance pricing and risk models, taking complex modeling problems from scoping through production deployment. While GLM-based pricing sits at the core of this role, you will also contribute to profitability and retention modeling, geospatial risk analysis, and the evaluation of emerging techniques like generative AI. You’ll partner closely with actuarial, product, and engineering teams to translate Porch’s unique property data into a durable competitive advantage in underwriting and pricing. This is an ideal role for an experienced practitioner who wants to deepen their technical expertise, support other data scientists, and drive measurable business value.
What You Will Do As A Senior Data Scientist, Insurance Pricing
Contribute to modeling standards and best practices for insurance pricing and risk modeling, helping the team apply them consistently
Support and mentor junior data scientists through code review, knowledge sharing, and technical guidance
Build, validate, and deploy GLM-based models (frequency, severity, and loss cost) for homeowners insurance pricing
Build machine learning models (GBMs, neural networks, etc.) that drive underwriting accuracy, competitive positioning, and profitability
Develop ensemble models predicting insured-level profitability, customer retention, and conversion, including customer lifetime value (LTV) models to prioritize marketing and underwriting strategies
Incorporate non-traditional data sources, including aerial imagery, satellite data, government records, and building permits, to quantify localized risk and inform pricing and underwriting decisions
Partner with product, actuarial, engineering, and business stakeholders to scope initiatives and integrate data science solutions into operational workflows
Work with the actuarial team to develop, file, implement, and monitor new predictive models that meet regulatory requirements
Follow rigorous deployment practices in high-traffic environments, including A/B testing, performance monitoring, and continuous refinement
Evaluate emerging techniques, including generative AI and LLMs, to identify new opportunities for competitive advantage
What You Will Bring As A Senior Data Scientist, Insurance Pricing
5+ years of experience in data science, with significant depth in insurance pricing or risk modeling
Track record of technical ownership, delivering complex projects end-to-end and supporting or mentoring less-experienced data scientists
Demonstrated experience building, validating, and deploying GLM-based pricing models in production, ideally for homeowners or other property/casualty lines, as well as machine learning models for non-pricing use cases
Proficiency in Python and SQL, with…