VP of Data Science

About The Company

Through a partnership-based approach, our client helps insurance professionals unlock untapped revenue in the small commercial space. With an innovative quoting platform that delivers accurate pricing and bindable quotes in less than one minute, our client makes small business insurance effortless. Our client is on a mission to build and foster a world-class team to bring speed, simplicity, and service to commercial insurance, valuing integrity, humility, passion, and intelligence, with the goal of reshaping a $200B+ market.

Job Summary

The VP, Data Science will lead our client's data science and research functions within the broader Data and Analytics (DnA) organization. This person will develop and mentor a team of highly technical individual contributors and people leaders while setting priorities for the design, documentation, review and delivery of high-quality data science products such as APIs, experiments, interactive data applications, predictive models, reports and automated workflows.

Key Responsibilities

• Own the roadmaps for the data science and research and development (R&D) subdomains of DnA
• Partner with key stakeholders in compliance, data, engineering, insurance, revenue and security to translate business needs into data science and R&D priorities
• Clearly communicate strategy, progress, risks and recommendations to executive audiences, technical teams and non-technical stakeholders
• Guide data science and R&D subdomains through complex tradeoffs involving business impact, explainability, regulatory considerations, rigor, scalability and speed
• Champion a culture of accountability, collaboration, continuous improvement and intellectual curiosity while ensuring the team remains focused on enterprise priorities rather than isolated technical outputs
• Serve as a senior-level people leader within DnA; responsible for career development, performance expectations and succession plans that support sustainable growth
• Evaluate and improve the tools, processes, metrics and partnerships needed to scale data science and R&D capabilities efficiently across the organization

Required Qualifications

• Master's degree or higher in Computer Science, Data Science, Economics, Engineering, Mathematics, Operations Research, Statistics or a related quantitative field
• 10+ years of professional data science experience
• 5+ years of experience managing data teams including coaching, hiring, leadership development, organizational design and performance management; demonstrated success establishing and maintaining accountability, scaling processes and teams
• Strong executive presence and communication skills including the ability to explain complex analytical concepts, model tradeoffs, research outcomes and strategic recommendations to senior stakeholders
• Deep understanding of the data science lifecycle including problem framing, exploratory analysis, experimentation, model development, testing, deployment, monitoring, governance and business impact measurement
• Strong cross-functional leadership skills with a track record of partnering effectively with compliance, data, engineering, insurance, revenue and security teams
• Technical fluency with technologies such as AWS/Azure/GCP, Databricks, Posit and scripting languages (Python, R, SQL)
• Technical fluency with topics such as AI agents and systems, experimental design, LLMs, MLOps, ModelOps

Bonus Skills/Experience

• Experience developing and deploying AI-based products in production
• Experience leading teams developing and deploying AI-based products in production
• Experience leading or partnering with applied research, experimentation, innovation or R&D teams that explore new data sources, methodologies and technologies
• Experience partnering with actuarial, claims, credit, pricing or underwriting teams
• Experience working in regulated industries such as banking, financial services, healthcare, insurance or related environments with meaningful audit, compliance, governance, and risk expectations