Clinical Research Associate - AI engineer

Overview

Role Overview

Key Responsibilities

• Lead clinical data strategy for AI platform development using PHI datasets (EHR, EMR, claims, registries, etc.)
• Design and oversee data analysis frameworks to extract clinically relevant insights
• Collaborate with data scientists, AI engineers, and product teams to translate clinical requirements into scalable AI models
• Ensure data quality, integrity, and clinical validity across all datasets and outputs
• Guide feature engineering and labeling processes for machine learning models
• Interpret AI model outputs and validate them against clinical standards and real-world evidence
• Ensure compliance with healthcare regulations and data privacy laws (HIPAA, GDPR, etc.)
• Develop clinical use cases such as predictive modeling, patient stratification, risk scoring, and decision support systems
• Contribute to research publications, validation studies, and regulatory documentation
• Act as subject matter expert (SME) in clinical research methodologies and healthcare data standards

Required Qualifications

• Advanced degree (MD, PhD, PharmD, or equivalent) in Clinical Research, Medicine, Public Health, or related field
• 5+ years of experience in clinical research, healthcare data analysis, or real-world evidence (RWE)
• Strong experience working with PHI data (EHR/EMR systems, clinical datasets)
• Solid understanding of clinical trial design, biostatistics, and epidemiology
• Familiarity with AI/ML concepts and their application in healthcare
• Experience collaborating with technical teams (data scientists, engineers)
• Knowledge of healthcare data standards (ICD, SNOMED, HL7, FHIR)
• Strong understanding of regulatory and compliance frameworks (HIPAA, GDPR)

Preferred Qualifications

• Experience in AI/ML healthcare product development
• Background in digital health, health tech startups, or SaaS platforms
• Programming or data analysis experience (Python, R, SQL)
• Experience with cloud-based healthcare data platforms
• Publications in peer-reviewed journals or involvement in clinical trials

Key Competencies

• Clinical insight with strong analytical thinking
• Ability to translate complex medical data into actionable insights
• Cross-functional collaboration and communication
• Problem-solving in ambiguous, data-heavy environments
• High attention to detail and data governance

What Success Looks Like

• Development of clinically robust AI models using PHI data
• High-quality, compliant, and scalable healthcare data pipelines
• Measurable improvements in healthcare outcomes or operational efficiency
• Strong alignment between clinical needs and AI capabilities

Compensation & Benefits

How To Apply