AVP, Business Intelligence & Analytics Engineering

CareSource

CareSource healthcare technology executive leading enterprise BI, data science, and AI/ML strategy. Driving compliant analytics, generative AI adoption, and measurable health-plan outcomes.

Posted 8/4/2026full-timeRemote • 🇺🇸 United StatesLead💰 $150,000 - $300,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in Business Intelligence, Analytics, and AI/ML strategy, governance, and execution within healthcare environments. Proficient in leading technical teams, developing advanced analytic models, and ensuring compliance with regulatory standards.

Highest-signal resume keywords

Data Analytics LeadershipAI/ML EngineeringPython ProgrammingHealthcare Data EcosystemsData Governance

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

PythonSQLRSASSparkMachine LearningStatistical ProgrammingData AnalyticsPredictive AnalyticsPrescriptive Analytics

Soft Skills

LeadershipOrganizational ManagementExecutive CommunicationCross-Functional CollaborationTalent Development

Tools & Technologies

DatabricksMLOpsCI/CDGenerative AILLMsRAG ArchitecturesVector Databases

Industry Keywords

HIPAA ComplianceCMS RegulationsHEDISICD-10CPTManaged CareHealth InsuranceData GovernanceQuality MonitoringVendor Risk Management

Tech Stack

Tools & technologies

PySparkPythonSparkSQL

About the role

Key responsibilities & impact

Own the enterprise Business Intelligence, Analytics, and Data Products strategy, governance, and multi-year roadmap
Partner with clinical, financial, operational, compliance, and technology stakeholders to define KPIs and self-service analytics capabilities
Establish data product standards, governance practices, and scalable delivery frameworks
Evaluate BI and analytics technologies and lead build-versus-buy recommendations
Ensure analytics and reporting comply with HIPAA, CMS, state regulatory, and enterprise governance requirements
Lead predictive and prescriptive analytics solutions for risk adjustment, quality improvement, population health, utilization management, care gap closure, fraud detection, and other priorities
Oversee development, deployment, optimization, monitoring, and lifecycle management of advanced analytic models
Build, lead, and develop an organization of BI developers, data engineers, data scientists, ML engineers, statisticians, and analytics professionals
Own the enterprise AI/ML platform strategy, architecture, governance, and evolution
Lead enterprise AI and generative AI use cases, including LLM and RAG solutions
Establish responsible AI governance covering model risk, fairness, explainability, bias monitoring, human oversight, ethics review, and audit readiness
Collaborate with Security, Compliance, Legal, Privacy, and Technology leadership on AI regulatory, security, auditability, and vendor risk requirements
Develop reusable AI frameworks, accelerators, governance standards, and enablement resources
Advise executive and Board-level stakeholders on analytics and AI strategy, performance, risks, opportunities, and business value
Own financial planning and budget accountability for the analytics, data science, and AI engineering portfolio
Foster innovation, continuous learning, experimentation, and responsible data- and AI-driven decision-making

Requirements

What you’ll need

Bachelor's degree in Computer Science, Statistics, Mathematics, Biomedical Informatics, or a related quantitative field required
Equivalent years of relevant work experience may be accepted in lieu of required education
Ten (10) years of progressive experience in data analytics, data science, or AI/ML engineering required
Four (4) years in a senior leadership role managing technical teams required
Advanced proficiency in Python, SQL, and statistical programming languages such as R or SAS
Experience with Spark/PySpark and modern machine learning frameworks
Familiarity with claims, clinical, HEDIS/Stars, HCC, and member data models
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
Knowledge of healthcare and managed care data ecosystems, including HL7/FHIR, ICD-10/CPT, NCQA HEDIS, CMS risk adjustment, and applicable regulations
Demonstrated leadership, talent development, organizational management, executive communication, and cross-functional collaboration capabilities
Experience in managed care, health plan, or health insurance environments preferred
Production AI/ML solutions experience in regulated, privacy-sensitive environments preferred
Databricks or equivalent modern lakehouse platform experience strongly preferred
Vendor evaluation, contract negotiation, and technology partnership management experience preferred
Data governance experience including cataloging, lineage, quality monitoring, and access control in a HIPAA-regulated context preferred
Ability to travel as required by business needs
No licensure or certification required

Benefits

Comp & perks

Remote work arrangement
Bonus tied to company and individual performance may be available
Substantial and comprehensive total rewards package
Employee total well-being support
Professional development, career development, and technical skill advancement opportunities