Senior Data Scientist

Description

The company 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, the company 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

Conditions

Workplace Type: Remote

Job Summary

The future is bright for the company, 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 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 11/6/2026 . Please know this may change based on business and interviewing needs.

At this time, the company 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 the company Team Member

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 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

What’s next?

Submit your application and our the company 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.