Data Science Manager, Insurance Pricing and Underwriting

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: Data Science Manager, Insurance Pricing and Underwriting
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 Data Science Manager, Insurance Pricing and Underwriting.
As the manager of our insurance pricing and underwriting data science team, you will directly lead a group of three to four data scientists building the models that determine how Porch prices and underwrites homeowners insurance. You will help shape priorities, develop talent, and stay close enough to the work to guide modeling decisions on our most complex and ambiguous problems, from business strategy through production deployment. While GLM-based pricing sits at the core of this role, your team’s work will extend across underwriting models, profitability and retention modeling, geospatial risk analysis, and the use of agentic workflows and generative AI in how models are built. You’ll partner closely with actuarial, product, and engineering leaders to translate Porch’s unique property data into a durable competitive advantage in underwriting and pricing. This is an ideal role for a hands-on technical leader who enjoys growing data scientists and wants to drive measurable business value at scale.
What You Will Do As A Data Science Manager, Insurance Pricing and Underwriting
Directly manage a team of 3–4 data scientists, including hiring, onboarding, goal setting, performance feedback, and career development
Contribute to the data science roadmap for pricing and underwriting models alongside the Head of Data Science, and drive the team’s execution against it, balancing delivery speed, model quality, and team capacity
Work with the Head of Data Science to set modeling standards and best practices, and provide technical review of model design, validation, and documentation across the team
Guide the development and deployment of GLM-based models (frequency, severity, and loss cost), built at the peril level, for homeowners insurance pricing
Oversee the development of the more advanced components of an insurance rating program, such as territory models, limit and deductible models, and other complex rating factors
Direct the build of machine learning models (GBMs, neural networks, etc.) that drive underwriting accuracy, competitive positioning, and profitability
Guide the development of ensemble models predicting insured-level profitability, customer retention, and conversion to inform underwriting and marketing strategies
Lead use of non-traditional data sources, including aerial imagery, satellite data, government records, and building permits, to quantify localized risk and inform strategic decisions
Partner with product, actuarial, engineering, and business leaders to scope high-priority 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
Establish the use of AI agents and agentic workflows for model-assisted development across the team, and evaluate emerging techniques including generative AI and LLMs to identify new opportunities for competitive advantage
What You Will Bring As A Data Science Manager, Insurance Pricing and Underwriting
8+ years of experience in data science, with significant depth in insurance pricing or risk modeling
Experience managing or leading data scientists, including hiring, coaching, and performance management
Hands-on experience building, validating, and deploying GLM-based pricing models (frequency, severity, and loss cost) in production, ideally for homeowners or other property/casualty lines
Proficiency in Python and SQL, with experience implementing GLMs and gradient boosting models (scikit-learn, statsmodels, xgboost, lightgbm)
Comfort using AI agents and agentic workflows for model-assisted development, and the ability to guide a team in using them effectively and responsibly
Experience with experimental design, including building, deploying, and A/B testing models in high-traffic environments, as well as causal analysis
Experience with cloud-based data platforms (e.g., BigQuery, GCP) and MLOps practices such as model training pipelines, versioning, and monitoring
Comfort with Git-based version control and collaboration tools such as GitHub or GitLab
Familiarity with the Atlassian suite of products (Confluence, Jira, etc.) for documentation and project tracking in an Agile/Scrum environment
Master’s or PhD in Statistics, Mathematics, Computer Science, or a related quantitative field preferred
Preferred: actuarial experience or an actuarial designation, including experience collaborating with actuarial teams on regulatory model filing
Nice to have: experience with territory modeling, limit and deductible modeling, and other advanced components of an insurance rating program
Nice to have: hands-on experience with LLMs, generative AI, or agentic AI, including prompt engineering, fine-tuning, or building agent-based workflows for insurance or financial services use cases
Nice to have: experience with geospatial or spatial data analysis (aerial imagery, satellite data, or property-level geographic datasets)
Nice to have: experience with model governance, validation frameworks, and regulatory compliance in insurance
The application window for this position is anticipated to close in 2 weeks (10 business days) from 11/9/2026. Please know this may change based on business and interviewing needs.
At this time, Porch Group does not consider applicants from the following states or jurisdictions for Remote positions: Alaska, Delaware, Hawaii, Mississippi, Nebraska, Montana, New Hampshire, West Virginia, or the District of Columbia.
What You Will Get As A Porch Group Team Member
Pay Range*: $187,500 – $262,500 annually
*Please know your actual pay at Porch will reflect a number of factors among which are your work experience and skillsets, job-related knowledge, alignment with market and our Porch employees, as well as your geographic location.
Additionally, you will be eligible to receive long-term incentive award

Skills
Python, Git, GCP, SQL, Machine Learning, Data Analysis, Generative AI, Agile, Scrum, Jira