Director of Analytics

Collective Health•San Francisco, CA

1d•$200,000 - $250,000•Hybrid

About The Position

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. About the Role 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.

Requirements

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
10+ years in healthcare analytics with 3+ years in claims processing analytics and 3+ years leading analytics teams
Proven transformation experience — has modernized or built an analytics function from scratch, not just managed inherited infrastructure
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)
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
Client-facing experience — comfortable presenting data to non-technical external audiences, navigating client escalations, and representing analytics in high-stakes conversations
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
People leadership depth — has hired, developed, and when necessary managed out; gives direct feedback and does not let performance issues linger
Bachelor's degree in a quantitative field (Statistics, Health Informatics, Computer Science, Actuarial Science, or similar); Master's preferred but not required

Nice To Haves

Experience with value-based care analytics or population health
Exposure to machine learning models and predictive analytics in a healthcare setting
Familiarity with data observability tooling (Monte Carlo, Great Expectations, or equivalent)
Experience with master data management and data architecture at scale

Responsibilities

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
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
Collaborate with senior leadership across Product, Operations, Engineering, Customer Success, and Customer Experience to align analytics initiatives with business priorities
Serve as a direct partner and analytics representative in client conversations, QBRs, and escalations — alongside CS, not behind them
Oversee end-to-end analysis of claims, member, and benefits data to surface trends, inefficiencies, and opportunities for cost savings or process improvement
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
Lead initiatives to improve claims adjudication accuracy, reduce denials, and enhance payment integrity
Drive AI-informed analytics — leveraging LLMs, RAG architecture, and generative AI tools to deliver smarter, faster insights at scale
Direct the development of dashboards, scorecards, and KPIs that monitor performance across the claims lifecycle and client experience
Establish and enforce data quality standards, metric governance, and documentation norms — so the same number means the same thing everywhere, every time
Build the data contract and observability framework that protects both the analytics team and its downstream consumers
Lead, mentor, and grow a high-performing analytics team with capabilities spanning data science, analytics engineering, reporting, and business intelligence
Set a high bar on delivery accountability — clear roadmaps, defined milestones, and a culture where commitments are kept
Foster an environment of continuous learning, direct feedback, and intellectual honesty
Ensure all analytics processes adhere to HIPAA and other regulatory requirements.
Identify and mitigate data risks, particularly in claims and member/provider data.