Staff Data Scientist, Insurance

<div class="content-intro"><h4><span style="color: rgb(0, 0, 0);">About us</span></h4> <p>Coalition is the world's first Active Insurance provider designed to help prevent digital risk before it strikes. Founded in 2017, Coalition combines comprehensive insurance coverage and innovative cybersecurity tools to help businesses manage and mitigate potential cyberattacks. </p> <p>Opportunities to make an impact with bold thinking are real—and happening daily at Coalition.</p></div><h4><span style="color: rgb(0, 0, 0);">About the role</span></h4> <p>We are hiring a Staff Data Scientist to define and lead the data science strategy for Coalition’s insurance business. In this role, you will own some of our most important analytical and modeling problems across underwriting, claims, CoalitionRe, and portfolio management helping us to move the organization from ad hoc analyses to reusable, rigorous decision frameworks.</p> <p>You’ll lead multi-quarter, cross-functional initiatives, design and analyze complex experiments and quasi-experiments, and build data and modeling assets that become the source of truth for leaders. Your work will shape how we measure performance, price and select risk, structure reinsurance, and allocate capital, while mentoring other scientists and analysts to raise the technical bar across the team.</p> <h4><span style="color: rgb(0, 0, 0);">Responsibilities</span></h4> <ul> <li>Define and lead the data science strategy for Coalition’s insurance business, driving multi-quarter initiatives across underwriting, claims, CoalitionRe, and portfolio management.</li> <li>Lead cross-functional analytics and data science projects that uncover insights and optimization opportunities across the end-to-end customer and broker journey, from submission through renewal and expansion.</li> <li>Provide technical leadership and guidance to other data scientists and senior analysts, setting a rigorous technical bar and developing repeatable frameworks (e.g., experimentation, causal analysis, model evaluation) that move the team away from one-off analyses.</li> <li>Design and analyze experiments and quasi-experiments (e.g., guideline changes, pricing strategies, broker programs), establishing best practices for test design, power, guardrails, and interpretation in low-frequency / high-severity insurance settings.</li> <li>Define, document, and maintain core insurance funnel and portfolio metrics (e.g., submission-to-bind, hit rate, loss ratio, frequency/severity, attachment points), and build automated dashboards and reporting used by leadership for decision-making.</li> <li>Develop data models and scalable analytical / ML workflows that improve reliability, repeatability, and time-to-insight for insurance stakeholders and downstream teams.</li> <li>Analyze disparate data sources (policy, exposure, pricing, claims, broker behavior, reinsurance, external data) and synthesize findings into clear, influential narratives with prioritized recommendations.</li> <li>Influence product, insurance, and revenue leadership with data-backed recommendations, shaping roadmaps, investment decisions, and OKR tracking.</li> <li>Mentor and uplevel junior and senior analysts/scientists, contributing to team best practices, code quality, documentation, and review processes; help shape the data science culture and career pathways.</li> <li>Champion innovation in methods and tooling, including causal inference, advanced statistical techniques, and appropriate application of ML/AI to unlock new capabilities and scale impact.</li> </ul> <h4><span style="color: rgb(0, 0, 0);">Skills and Qualifications</span></h4> <ul> <li>10+ years in analytics or data science with a consistent track record of measurable product, underwriting, or revenue impact.</li> <li>Deep domain experience (8+ years) in the Insurance industry, ideally PC or cyber/EO, working closely with underwriting, claims, actuarial/portfolio, or reinsurance teams.</li> <li>Expert SQL, including comp ... (truncated, view full listing at source)