Ready for your next chapter? Build the future of insurance with a team that values simplicity, empathy, and innovation. Openly is redefining the insurance experience, replacing decades of complexity with clarity and modern technology. We’re the insurance provider people trust and the partner independent agents choose. What Sets Us Apart • Technology that delivers: We use data to modernize underwriting and deliver tailored insurance solutions that fit how people actually live. • Superior protection: Highly customizable coverage designed around what policyholders need. • Effortless from quote to claim: Simple, intuitive workflows for independent agents and fast, human-centered care for policyholders. Our Core Values Our people are as important as our product. Collaboration, open communication, and work-life balance aren't just nice-to-haves, they’re at the core of how we operate. We look for people driven by integrity, empathy, teamwork, curiosity, and urgency, because a great company starts with the right people. Diversity, Equity, & Inclusion We embrace individuality because everyone deserves to work somewhere they belong. We’re committed to building an inclusive culture that spans race, gender, age, religion, identity, and background. Job Details As VP, Insurance Data Science, you'll set the strategic direction for how data science is applied across our insurance product — spanning the cost and demand modeling functions that shape our pricing and underwriting algorithms, and growth levers — while managing and developing the people who execute that vision. This is a role for a leader who is technically deep enough to set a high bar, people-focused enough to build a team that clears it, and commercially minded enough to connect modeling decisions to business outcomes. You'll report directly to the Chief Insurance Product Officer and serve as a key voice in how Openly builds and deploys its analytical edge. Responsibilities Strategy & Leadership • Own the vision and delivery of Openly's data science capabilities — prioritizing initiatives that drive pricing precision, underwriting performance, and profitable growth. • Partner with pricing, underwriting, product, and engineering leadership to ensure data science efforts are tightly integrated with business strategy and operational workflows. • Serve as Openly's insurance product authority on data science methodology — staying current on advances in ML, AI, and insurance-specific modeling practice and bringing the right innovations to the team with rigor and judgment. • Represent Insurance Data Science in senior leadership conversations, translating complex modeling work into clear implications for business performance. Modeling & Research • Set the technical standard for Openly's cost and demand modeling suite — including GLMs, gradient boosting, neural approaches, and other ML methods — ensuring models are well-validated, production-ready, and coherent with actuarial frameworks. • Drive the modeling strategy for new initiatives across existing and expansion states, spanning both homeowners and personal auto product lines, ensuring data science capabilities scale with the business. • Govern the model lifecycle — from development through validation, deployment, monitoring, and refresh — establishing clear standards for when models are production-ready and when they need to be revisited. • Collaborate closely with actuaries to ensure model outputs can be operationalized within regulatory and pricing frameworks. • Advance Openly’s data science capabilities through collaborative strategic research with Data/Machine Learning Engineering Engineering & Standards • Collaborate with engineering dept leadership on shared development standards — code quality, version control, peer review, testing, reproducibility, and documentation. • Ensure the Insurance Data Science team can operate at the right pace and scale through strategic investments in infrastructure, tooling, and access. • Actively partner with Data/ML Engineering to design, prioritize, and implement capabilities critical to scale • Evaluate and introduce new tools, platforms, and data sources with a bias toward practical impact over novelty. People Leadership • Lead, expand, and develop the Insurance Data Science team — including senior data scientists, managers, and analysts — setting clear role expectations, investing in career growth, supporting the recruiting and hiring of external talent, and building a culture of technical excellence and intellectual rigor. • Own hiring and team structure decisions in partnership with the CIPO, building the capabilities Openly needs now and over the next several years. • Mentor senior individual contributors and managers, developing the next generation of data science leadership within the organization. Key Requirements • 15+ years of experience in data science or a closely related quantitative/actuarial field, with at least 8 years in a leadership role managing highly analytical teams. • Deep technical fluency in predictive modeling — GLMs, gradient boosting, and modern ML methods — with demonstrated experience delivering production models in a regulated, data-intensive industry. • Proven experience across both cost modeling (loss ratio, frequency, severity, pure premium) and demand modeling (conversion, retention, price elasticity), and the strategic judgment to prioritize across a portfolio of modeling initiatives. • Extensive experience in personal lines insurance with models directly driving pricing and underwriting decisions; familiarity with the actuarial context in which data science operates is a strong differentiator. • Track record of building and leading high-performing data science teams — not just managing delivery, but developing people, raising the technical bar, and creating an environment where rigorous analytical work thrives. • Strong communicator and cross-functional collaborator, equally fluent in technical depth with data scient