Director of Analytics

R1 RCM•Remote, TN, TN

1d•$117,000 - $194,847•Remote

About The Position

R1 is the leading provider of technology-driven solutions that transform the patient experience and financial performance of hospitals, health systems, and medical groups. We are the one company that combines the deep expertise of a global workforce of revenue cycle professionals with the industry’s most advanced technology platform, encompassing sophisticated analytics, AI, intelligent automation, and workflow orchestration. The Director of Analytics is a senior technical and business leader responsible for shaping the vision, architecture, and delivery of advanced analytics capabilities that power physician enterprise performance. This leader drives the design and implementation of scalable data platforms, modern analytics tooling, and intelligent data products that enable actionable insights across complex healthcare operations. This role partners closely with senior leadership across clients, operations, product, engineering, and strategy to translate business needs into robust, scalable, and secure analytics solutions. The Director is accountable for distilling a broad constellation of stakeholder needs into a cohesive, technically sound roadmap focused on data platform modernization, advanced analytics, AI-driven insights, and self-service enablement. Success requires a blend of technical depth, analytical thinking, and client-centric innovation, with the ability to overcome data limitations and deliver high-impact analytics solutions at scale.

Requirements

10+ years in healthcare analytics or data platform roles, with strong experience in physician group operations or healthcare technology.
Proven success leading technically sophisticated analytics organizations and delivering scalable data solutions.
Deep expertise in: Data architecture (warehouses, lakes, semantic layers), SQL and performance optimization, BI platforms (Tableau, Power BI, or similar), Data pipeline and ETL/ELT design.
Experience working in cloud-based data environments (e.g., Azure, AWS, or GCP).
Familiarity with AI/ML applications in healthcare analytics and predictive modeling.
Demonstrated ability to translate business needs into technical solutions and scalable data products.
Exceptional leadership, communication, and stakeholder management skills.

Responsibilities

Lead the evolution from traditional reporting to modern, product-oriented data and analytics capabilities, including data products, APIs, and embedded analytics.
Oversee the development of scalable, cloud-based analytics environments, including data lakes, warehouses, semantic layers, and BI ecosystems.
Drive adoption of AI/ML, predictive analytics, and intelligent automation to optimize physician productivity, coding quality, and revenue performance.
Establish standards for data modeling, pipeline design, performance optimization, and observability across analytics systems.
Partner deeply with data engineering and product teams to design and deliver resilient, high-performance data pipelines across EMR, billing, coding, and third-party systems.
Influence enterprise data architecture decisions, including tooling, cloud strategy, and integration patterns.
Ensure analytics solutions are built on trusted, governed, and well-documented data assets.
Drive adoption of modern development practices (CI/CD, version control, testing frameworks) within analytics teams.
Lead and mentor a multidisciplinary team including analytics/ BI developers, data analysts, and visualization specialists.
Build technical depth across the team in areas such as data modeling, SQL optimization, BI performance tuning, and data storytelling.
Establish a technical leadership bench, including tech leads and domain experts.
Foster a culture of innovation, experimentation, and analytics excellence, alongside client-centric delivery.
Deliver executive-level dashboards, KPIs, and advanced analytics supporting leaders and ELT.
Develop scalable analytics solutions to monitor: AR performance and trends, Payer denials and root-cause drivers, Physician productivity (RVUs, utilization), Coding accuracy and acuity, Patient financial engagement and payment behavior.
Translate complex data into clear, actionable insights and decision frameworks.
Enable self-service analytics ecosystems that empower stakeholders while ensuring governance and consistency.
Partner with commercial and client teams to translate analytics capabilities into differentiated, technology-forward offerings.
Provide input into data integration strategy, technical feasibility, and analytics requirements during client onboarding and contracting.
Establish and enforce enterprise data governance frameworks, including data quality standards, lineage, and stewardship.
Ensure compliance with healthcare data regulations (e.g., HIPAA) and enterprise security standards.
Drive consistency in metric definitions, semantic layers, and reporting standards across the organization.