Senior Business Intelligence Specialist, Revenue Cycle

At CVS Health, we’re building a world of health around every consumer and surrounding ourselves with dedicated colleagues who are passionate about transforming health care.

As the nation’s leading health solutions company, we reach millions of Americans through our local presence, digital channels and more than 300,000 purpose-driven colleagues – caring for people where, when and how they choose in a way that is uniquely more connected, more convenient and more compassionate. And we do it all with heart, each and every day.

Job Summary:

The AI lead, leads the development and deployment of end-to-end AI and Machine Learning (ML) pipelines, ensuring that AI initiatives align with strategic business goals. This role requires a combination of expertise in Revenue Cycle Management (RCM) with advanced AI and machine learning technologies to optimize processes, improve operational efficiency, and drive enhanced financial performance. This high-level, strategic role requires a professional to bridge the gap between business objectives and technical AI capabilities.

Strong leadership to guide-cross-functional teams, including IT, Finance, Operations, and Data Analytic departments, to design, implement, and scale AI-powered processes that improve revenue cycle outcomes. You will be a key player in elevating our RCM processes, ensuring automation, reducing manual workloads, and enhancing accuracy through advanced technologies.

Key Responsibilities:

Strategic Planning and AI–Process Architectural Design:

• Design and develop scalable, secure, and resilient AI systems and infrastructure.
• Translate business needs and use cases into technical AI and ML solutions.
• Evaluate and select the most appropriate AI technologies, frameworks, and cloud services

Technical Implementation and Oversight:

• Oversee the entire lifecycle of AI projects, from research and design to deployment and monitoring.
• Collaborate with data scientists and engineers to build robust data pipelines for AI model training and inference.
• Ensure the seamless integration of AI applications and ML models with existing IT infrastructure and business processes.
• Optimize AI systems for performance, scalability, and cost efficiency, and troubleshoot technical issues. 

Leadership and Collaboration:

• Provide technical leadership and guidance to development teams, including AI engineers and software developers.
• Collaborate effectively with business stakeholders, product managers, and executives to communicate the potential, limitations, and strategic value of AI initiatives.
• Foster a culture of innovation and continuous improvement across AI teams. 

Governance and Ethics

• Ensure AI implementations comply with ethical standards, data privacy regulations (e.g., GDPR), and security best practices.
• Establish and enforce data governance policies for AI model development and data usage.
• Mitigate risks such as adversarial attacks and data poisoning. 

Research and Development

• Stay up to date with the latest advancements in AI research, trends, and technologies.
• Recommend new methodologies and tools to improve the organization's AI capabilities. 

Education:

• High School Diploma required; Bachelor’s degree preferred in Computer Science, Healthcare Informatics, Data Science, or a related field.

Required Qualifications:

• Minimum 3 years of experience in business intelligence development, data warehousing, or related fields.
• Proven track record of designing, implementing, and deploying scalable AI/ML solutions in a production environment.
• Demonstrated experience with cloud computing platforms (AWS, Azure, GCP) and MLOps practices. 
• Applying Agile/SAFe methodologies and contributing to architecture-level discussions
• Excellent communication and interpersonal skills, with the ability to work collaboratively with stakeholders across the organization.

Preferred Qualifications:

• Familiarity with specialty pharmacy or healthcare data.
• Demonstrated leadership and project management capabilities to guide and mentor teams.
• Deep understanding of machine learning models, neural networks, natural language processing (NLP), and computer vision. 
• Proficiency in Python, Dataiku or R Studio.
• Strong SQL skills and experience with data aggregation and data modeling.
• Experience with Tableau, Power BI