Director of AI and Analytics

Coral Care•Washington, DC

7d•$160,000 - $190,000•Hybrid

About The Position

Coral Care is a rapidly scaling Series A platform that simplifies in-home pediatric therapy for families and ensures financial sustainability for clinicians. We provide the essential infrastructure for their practices and are expanding nationwide. Analytics and AI are fundamental to our decision-making, operational efficiency, and the growth of our marketplace. This role requires a blend of technical expertise and strategic leadership, placing you at the center of how we leverage data and AI across the company. You will be responsible for everything from executive reporting and automated workflows to the systems powering our operations. Reporting directly to the Cofounder and COO, you will collaborate cross-functionally with all teams. This Director-level position demands proficiency in SQL, workflow automation, AI bot deployment, team leadership, influencing senior executives, and effectively communicating insights. In our early-stage environment, you will utilize AI to enhance speed, efficiency, and impact.

Requirements

Eight to twelve or more years in analytics, data science, or technical roles, with progression in scope and responsibility.
Marketplace experience is required; demonstrated ability to model or operate within a two-sided marketplace and understand the interplay of supply, demand, conversion, and matching.
Mastery of SQL and Snowflake for data extraction and analysis.
Fluency with BI and data visualization tools (e.g., Google Sheets, Metabase, or equivalent) for building executive-grade dashboards.
Hands-on experience building with LLMs and AI tooling, including automating workflows using language model APIs and integrating with external systems.
Track record of building automations that connect internal processes to external APIs and vendor systems.
Strong written communication and data storytelling skills.
Excellent cross-functional stakeholder management and organizational skills.
Experience managing or mentoring junior analysts or data professionals.

Nice To Haves

Python proficiency for data processing, pipeline automation, and LLM application development.
Google Apps Script experience for Sheets-based automation and workflow tooling.
Background in strategic finance or FP&A, with the ability to build business cases and model scenarios with sensitivity analyses.
Familiarity with healthcare data, including claims, credentialing, or payer data structures.
Early-stage or growth-stage startup experience, with a proven ability to build in the absence of established playbooks.

Responsibilities

Own the strategic analytics function end-to-end, defining key questions, building reliable infrastructure, developing tools to identify problems, and translating results into business decisions.
Define and maintain core business metrics, dashboards, and the executive reporting suite.
Lead open-ended analytical work across supply, demand, clinical operations, finance, marketplace matching, acquisition, and other business growth areas.
Own the BI and data visualization layer, ensuring insights are accessible across teams.
Partner with the COO on strategic FP&A modeling, scenario analysis, and business case development.
Serve as the company's analytical conscience, identifying potential second- and third-order effects of decisions.
Deeply understand marketplace dynamics and build analytical frameworks to model the impact of changes in supply, demand, pricing, matching, or geography.
Own marketplace health metrics such as match rates, provider utilization, demand coverage, and funnel conversion.
Model the secondary and tertiary effects of operational changes and provide strategic recommendations to the executive leadership team.
Identify structural imbalances in supply and demand across geography, specialty, payer, and patient segments.
Support market expansion decisions with rigorous data analysis.
Build AI-powered systems to enhance operational speed and intelligence, focusing on removing bottlenecks in human effort.
Define and execute an AI and automation roadmap, prioritizing high-leverage operational needs in collaboration with the engineering team.
Build LLM-powered workflows to automate repeatable tasks in operations, credentialing, RCM, and clinical support.
Develop and maintain integrations with external vendors, APIs, and data sources.
Evaluate and deploy AI tooling to extend team capacity without increasing headcount.
Inform product development by identifying opportunities for AI-powered features to improve user experience.
Manage a team of two analysts, acting as a player-coach.
Set analytical standards, review frameworks, and development priorities for direct reports.
Create leverage through delegation while maintaining accountability for quality and output.
Foster a team culture that values both rigor and speed.