Job 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. 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: Staff 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 Staff Data Scientist, Insurance Pricing. As one of the most senior individual contributors on our data science team, you will set technical direction for how Porch approaches homeowners insurance pricing and risk modeling, owning our most complex and ambiguous modeling problems end-to-end — from business strategy through production deployment. While GLM-based pricing sits at the core of this role, your influence will extend across profitability and retention modeling, geospatial risk analysis, and the adoption of emerging techniques like generative AI. 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 seasoned practitioner who wants to shape strategy, mentor other data scientists, and drive measurable business value at scale. What You Will Do As A Staff Data Scientist, Insurance Pricing Set the technical vision for insurance pricing and risk modeling, establishing best practices and modeling standards across the team Provide technical oversight and mentorship to other data scientists Architect 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 Lead use of non-traditional data sources — aerial imagery, satellite data, government records, 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 Champion rigorous deployment practices in high-traffic environments, including A/B testing, performance monitoring, and continuous refinement Drive a culture of experimentation, evaluating emerging techniques including generative AI and LLMs to identify new opportunities for competitive advantage What You Will Bring As A Staff Data Scientist, Insurance Pricing 10 years of experience in data science, with significant depth in insurance pricing or risk modeling Track record of technical leadership — setting direction on complex projects, establishing standards, and mentoring or providing technical oversight to other data scientists Demonstrated expertise architecting, 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 experience implementing GLMs and gradient boosting models (scikit-learn, statsmodels , xgboost , lightgbm ) 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 Proficiency with Confluence and Jira 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 Nice to have: background in actuarial science or insurance mathematics, including experience collaborating with actuarial teams on regulatory model filing Nice to have: experience with customer lifetime value, retention, or conversion modeling Nice to have: experience with geospatial or spatial data analysis (aerial imagery, satellite data, or property-level geographic datasets) Nice to have: exposure to generative AI and LLMs, including prompt engineering or fine-tuning for insurance or financial services use cases Nice to have: exposure to experimentation frameworks and causal inference methods 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 8/27/2026. 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*: $168,800 – $236,300 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 awards, subject to program guidelines and approvals. Our benefits package will provide you with comprehensive coverage for your health, life, and financial wellbeing. Our traditional healthcare benefits include three (3) Medical plan options, two (2) Dental plan options, and a Vision plan from which to choose. Critical Illness, Hospital Indemnity and Accident plans are offered on a voluntary basis. We offer pre-tax savings options including a partially employer funded Health Savings Account and employee Flexible Savings Accounts including healthcare, dependent care, and transportation savings options. We provide company paid Basic Life and AD&D, Short and Long-Term Disability benefits. We also offer Voluntary Life and AD&D plans. Both traditional and Roth 401(k) plans are available with a discretionary employer match . Supportlinc is part of our employer paid wellbeing program and provides employees and their families access to on demand guided meditation and mindfulness exercises, mental health coaching, clinical care and online access to confidential resources including will preparation. LifeBalance is a free resource to employees and their families for year-round discounts on things like gym memberships, travel, appliances, movies, pet insurance and more. Our wellness programs include flexible paid vacation, company-paid holidays of typically nine per year, paid sick time, paid parental leave, identity theft program, travel assistance , and fitness and other discounts programs. #LI-NH1 #LI-Remote What’s next? Submit your application and our Porch Group Talent Acquisition team will be reviewing your application shortly! If your resume gets us intrigued, we will look to connect with you for a chat to learn more about your background, and then possibly invite you to have virtual interviews. What s important to call out is that we want to make sure not only that you re the right person for us, but also that we re the right next step for you, so come prepared with all the questions you have! Porch is committed to building an inclusive culture of belonging that not only embraces the diversity of our people but also reflects the diversity of the communities in which we work and the customers we serve. We know that the happiest and highest performing teams include people with diverse perspectives that encourage new ways of solving problems, so we strive to attract and develop talent from all backgrounds and create workplaces where everyone feels seen, heard and empowered to bring their full, authentic selves to work. Porch is an Equal Opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex including sexual orientation and gender identity, national origin, disability, protected veteran status, or any other characteristic protected by applicable laws, regulations, and ordinances. Porch Group is an E-Verify employer. E-Verify is a web-based system that allows an employer to determine an employee s eligibility to work in the US using information reported on an employee s Form I-9. The E-Verify system confirms eligibility with both the Social Security Administration (SSA) and Department of Homeland Security (DHS). For more information, please go to the USCIS E-Verify website .

Requirements

Must-haves

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: Staff Data Scientist, Insurance Pricing
Location: United States
Workplace Type: Remote
The future is bright for the Porch Group, and we’d love for you to be a part of it as our Staff Data Scientist, Insurance Pricing.
What You Will Do As A Staff Data Scientist, Insurance Pricing
Set the technical vision for insurance pricing and risk modeling, establishing best practices and modeling standards across the team
Provide technical oversight and mentorship to other data scientists
Architect 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
Lead use of non-traditional data sources — aerial imagery, satellite data, government records, 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
Champion rigorous deployment practices in high-traffic environments, including A/B testing, performance monitoring, and continuous refinement
Drive a culture of experimentation, evaluating emerging techniques including generative AI and LLMs to identify new opportunities for competitive advantage
What You Will Bring As A Staff Data Scientist, Insurance Pricing
10 years of experience in data science, with significant depth in insurance pricing or risk modeling
Track record of technical leadership — setting direction on complex projects, establishing standards, and mentoring or providing technical oversight to other data scientists
Proficiency in Python and SQL, with experience implementing GLMs and gradient boosting models (scikit-learn, statsmodels , xgboost , lightgbm )
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
Proficiency with Confluence and Jira for documentation and project tracking in an Agile/Scrum environment

Nice-to-haves

Master’s or PhD in Statistics, Mathematics, Computer Science, or a related quantitative field preferred

Application prep

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Keywords to mirror

aimachine learningpythonsqlgcpjiraagilescrumgo

Platform: workday
Effort: long

Benefits

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Dental

Vision

401(K)

Parental Leave

Wellness