AVP, Business Intelligence & Analytics Engineering

This is a fully remote position, open to applicants in United States.

📋 Description

• Take charge of the enterprise Business Intelligence, Analytics, and Data Products strategy, governance, and multi-year roadmap.

• Collaborate with clinical, financial, operational, compliance, and technology stakeholders to establish KPIs and self-service analytics capabilities.

• Set standards for data products, governance practices, and scalable delivery frameworks.

• Assess BI and analytics technologies and lead recommendations on build versus buy decisions.

• Ensure that analytics and reporting adhere to HIPAA, CMS, state regulatory, and enterprise governance standards.

• Spearhead predictive and prescriptive analytics solutions for risk adjustment, quality enhancement, population health, utilization management, care gap closure, fraud detection, and other key priorities.

• Supervise the development, deployment, optimization, monitoring, and lifecycle management of advanced analytic models.

• Build, lead, and nurture a team of BI developers, data engineers, data scientists, ML engineers, statisticians, and analytics professionals.

• Own the enterprise AI/ML platform strategy, architecture, governance, and ongoing evolution.

• Manage enterprise AI and generative AI use cases, including LLM and RAG solutions.

• Implement responsible AI governance that encompasses model risk, fairness, explainability, bias monitoring, human oversight, ethics review, and audit readiness.

• Work in partnership with Security, Compliance, Legal, Privacy, and Technology leadership to address AI regulatory, security, auditability, and vendor risk requirements.

• Create reusable AI frameworks, accelerators, governance standards, and enablement resources.

• Provide guidance to executive and Board-level stakeholders regarding analytics and AI strategy, performance, risks, opportunities, and business value.

• Manage financial planning and budget responsibilities for the analytics, data science, and AI engineering portfolio.

• Promote innovation, continuous learning, experimentation, and responsible data- and AI-driven decision-making.

⛳️ Requirements

• A Bachelor’s degree in Computer Science, Statistics, Mathematics, Biomedical Informatics, or a related quantitative field is required.

• Equivalent years of relevant work experience may be accepted in place of the required education.

• A minimum of ten (10) years of progressive experience in data analytics, data science, or AI/ML engineering is required.

• At least four (4) years in a senior leadership role overseeing technical teams is necessary.

• Advanced proficiency in Python, SQL, and statistical programming languages such as R or SAS is essential.

• Experience with Spark/PySpark and contemporary machine learning frameworks is required.

• Familiarity with claims, clinical, HEDIS/Stars, HCC, and member data models is preferred.

• A solid understanding of AI/ML and MLOps, including model lifecycle management, monitoring, CI/CD, experiment tracking, generative AI, LLMs, prompt engineering, RAG architectures, and vector databases is crucial.

• Knowledge of healthcare and managed care data ecosystems, including HL7/FHIR, ICD-10/CPT, NCQA HEDIS, CMS risk adjustment, and relevant regulations is important.

• Proven leadership, talent development, organizational management, executive communication, and cross-functional collaboration skills are necessary.

• Experience in managed care, health plan, or health insurance environments is preferred.

• Background in production AI/ML solutions within regulated, privacy-sensitive environments is preferred.

• Experience with Databricks or an equivalent modern lakehouse platform is strongly preferred.

• Vendor evaluation, contract negotiation, and technology partnership management experience are preferred.

• Experience in data governance, including cataloging, lineage, quality monitoring, and access control in a HIPAA-regulated context is preferred.

• Willingness to travel as required by business needs.

• No specific licensure or certification is required.

🏝️ Benefits

• Flexible remote work arrangement.

• Potential for a bonus linked to company and individual performance.

• Comprehensive and substantial total rewards package.

• Employee well-being support for total health.

• Opportunities for professional development, career advancement, and technical skill enhancement.