Director of Analytics

Location: San Francisco, US
Employment: Contract
Posted: 1mo ago

Data Ai AnalyticsAnalysis InsightAi Ml Data

About this role

<div class="content-intro">At Collective Health, we’re transforming how employers and their people engage with their health benefits by seamlessly integrating cutting-edge technology, compassionate service, and world-class user experience design.</div><h3>About the Role</h3> We are looking for a Director of Analytics to lead our healthcare analytics function through a pivotal transformation. This is not a steady-state management role — we are modernizing our client reporting infrastructure from the ground up, and you will own that mandate from vision to delivery. You will lead a team of analysts, partner closely with Customer Success, Customer Experience, and Data Engineering, and serve as the primary analytics thought partner to our internal and external stakeholders — including direct engagement with clients. The right person brings deep healthcare data expertise, a builder's mindset, and the credibility to earn trust with both technical teams and business partners quickly. This role sits at the center of how Collective Health uses data to serve its clients. Done well, it changes how our clients experience their benefits — and how our internal teams make decisions. <h3>What you’ll do:&nbsp;</h3> Strategic Leadership <ul> <ul> <li>Own the analytics strategy and roadmap — not just maintain it; build it from a clear-eyed assessment of current state and a sharp view of where the function needs to go</li> <li>Lead Client Reporting 2.0: audit what exists, design a modern replacement, and deliver an automated, scalable reporting infrastructure that clients trust and CS can stand behind</li> <li>Collaborate with senior leadership across Product, Operations, Engineering, Customer Success, and Customer Experience to align analytics initiatives with business priorities</li> <li>Serve as a direct partner and analytics representative in client conversations, QBRs, and escalations — alongside CS, not behind them</li> </ul> </ul> Analytics&nbsp; <ul> <ul> <li>Oversee end-to-end analysis of claims, member, and benefits data to surface trends, inefficiencies, and opportunities for cost savings or process improvement</li> <li>Shift the analytics function from reactive (answering requests) to proactive — surfacing insights that inform product, CS strategy, and executive decision-making before someone has to ask</li> <li>Lead initiatives to improve claims adjudication accuracy, reduce denials, and enhance payment integrity</li> <li>Drive AI-informed analytics — leveraging LLMs, RAG architecture, and generative AI tools to deliver smarter, faster insights at scale</li> <li>Data Management &amp; Reporting</li> <li>Direct the development of dashboards, scorecards, and KPIs that monitor performance across the claims lifecycle and client experience</li> <li>Establish and enforce data quality standards, metric governance, and documentation norms — so the same number means the same thing everywhere, every time</li> <li>Build the data contract and observability framework that protects both the analytics team and its downstream consumers</li> </ul> </ul> Team Development <ul> <ul> <li>Lead, mentor, and grow a high-performing analytics team with capabilities spanning data science, analytics engineering, reporting, and business intelligence</li> <li>Set a high bar on delivery accountability — clear roadmaps, defined milestones, and a culture where commitments are kept</li> <li>Foster an environment of continuous learning, direct feedback, and intellectual honesty</li> </ul> </ul> Compliance &amp; RiskEnsure all analytics processes adhere to HIPAA and other regulatory requirements.Identify and mitigate data risks, particularly in claims and member/provider data. To be successful in this role, you’ll need: Required <ul> <li>Healthcare domain expertise — deep, working knowledge of claims data, member data, payer-provider models, and the regulatory environment (HIPAA, ICD, CPT, HCPCS, HL7, EDI 837); this is required, not preferred</li> <li>10+ years in healthcare analytics with 3+ years in claims processing analytics and 3+ years leading analytics teams</li> <li>Proven transformation experience — has modernized or built an analytics function from scratch, not just managed inherited infrastructure</li> <li>Technical fluency in the modern data stack — Looker (or equivalent BI platform), SQL, dbt, cloud data warehouse (Snowflake, Databricks, or BigQuery), orchestration tooling (Airflow or equivalent)</li> <li>AI / ML literacy — working familiarity with LLMs, RAG architecture, and generative AI tools (Google Vertex, OpenAI, or equivalent); able to guide the team on applied AI use cases without needing to build models personally</li> <li>Client-facing experience — comfortable presenting data to non-technical external audiences, navigating client escalations, and representing analytics in high-stakes conversations</li> <li>Startup operating experience — has worked in a fast-moving, high-ambiguity environment; understands that speed, responsiveness, and ownership look different at a startup than at a large enterprise</li> <li>People leadership depth — has hired, developed, and when necessary managed out; gives direct feedback and does not let performance issues linger</li> <li>Bachelor's degree in a quantitative field (Statistics, Health Informatics, Computer Science, Actuarial Science, or similar); Master's preferred but not required</li> </ul> <h4>Preferred:</h4> <ul> <li>Experience with value-based care analytics or population health</li> <li>Exposure to machine learning models and predictive analytics in a healthcare setting</li> <li>Familiarity with data observability tooling (Monte Carlo, Great Expectations, or equivalent)</li> <li>Experience with master data management and data architecture at scale</li> </ul> <h3>Key Competencies</h3> <ul> <li>Delivery Accountability — owns a roadmap, manages dependencies, ships without needing consta

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