Business Analyst – Healthcare Data and Systems at IQVIA

Role Summary/Overview:

• This mid-level position provides broad analyst support in the end-to-end design, development, implementation, deployment, and maintenance of robust healthcare data collection and processing systems. These systems are intended for and support critical observational studies, including population health, disease monitoring, clinical trials, and health surveillance. The Business Analyst under general supervision will support the entire lifecycle of these systems, working with product team members to ensure effective analysis and project execution, including data analysis. The goal is to deliver solutions that are efficient, scalable, maintainable, and meet stakeholder needs.

Required Qualifications:

Education & Experience:

• Bachelor's degree in Health Informatics, Computer Science, or a related field (or equivalent experience).
• 2+ years of hands-on experience in business analysis, implementing healthcare-related data and/or processing systems, such as clinical trial management software, LIMS, or EDCs, preferably for observational studies.

Healthcare Data Expertise:

• Proficiency in data modeling (relational and non-relational) and applying various healthcare data models (e.g., HL7 FHIR, OMOP) to solve practical problems.
• Demonstrated knowledge and practical application of healthcare data standards, particularly HL7 (especially FHIR).
• Proven ability to work with, describe, convert, and/or integrate idiosyncratic or custom data models into standard formats.

Technical & Analytical Acumen:

• Experience with business analysis applications for analysis, presentations, and requirements documentation (such as Excel, PowerPoint, Jira, Confluence, Aha, mind mapping or process flow applications).
• Demonstrated ability to understand client requirements as well as underlying infrastructure applications, systems, and processes to enable execution of those skills.
• Proven ability to troubleshoot and resolve complex technical problems in healthcare data systems and integration, with general guidance.
• Strong analytical and problem-solving skills, with a focus on healthcare data challenges.
• Proficiency with distributed version control systems, preferably Git, for collaborative development and documentation.

Communication & Project Management Skills:

• Excellent written and verbal communication skills, capable of explaining moderately complex technical healthcare data concepts clearly and concisely to both technical and non-technical audiences.
• Ability to work independently, balance multiple priorities, and support project teams to successful project completion in the context of healthcare data projects.
• Effective in rapidly producing clear, concise, and accurate standard business documentation and various diagram types (e.g., ERDs, flowcharts, sequence diagrams), understanding the appropriate use for each and the ability to use a combination of multiple diagram types to describe moderately complex business processes accurately and comprehensively.

Healthcare Domain Knowledge:

• Familiarity with the U.S. healthcare system, including its data structures, standards, and key initiatives.
• Experience with data management requirements and considerations for human subjects research, especially longitudinal studies.
• Knowledge of good data management practices for scientific datasets (ensuring integrity, security, and HIPAA compliance).

Adaptability & Learning:

• Demonstrated ability to quickly learn and master new, highly detailed, domain-specific knowledge (e.g., Quality Payment Program) and apply it to implementation projects, becoming a subject matter expert on regularly changing programs.

Key Responsibilities:

• Work with senior analysts and the project manager to execute the full lifecycle of study and registry product implementation projects, supporting their completion on-time, on-budget, and in accordance with stakeholder requirements. Under general direction, formulate and define systems scope and objectives based on both user needs and a good understanding of applicable business systems and requirements.
• Implement real world evidence systems in alignment with product capabilities and client protocols.
• Work collaboratively with epidemiology and data management teams to document product configuration, identify configuration gaps, and apply healthcare data models and standards (e.g., HL7 FHIR, OMOP) under advisement by medical sciences and data analysts.
• Document data collection and integration requirements to meet study and regulatory needs. Assess and prioritize requirements for configuration. Document user stories, maintain good documentation practices, and support engineering teams in executing projects using agile and hybrid methodologies.
• Ensure good data management practices are maintained for healthcare datasets intended for scientific use, maintaining data integrity, security, and HIPAA compliance.
• Project Execution & Solution Delivery: Support the full lifecycle of healthcare data system implementation projects, enabling their completion on-time, on-budget, and in accordance with stakeholder requirements. Identify and triage issues and escalate to higher-level analysts or business team for prioritization.

Data Modeling, Analysis & Management:

• Under general guidance, conduct and document specified data modeling, encompassing both relational and non-relational approaches.
• Perform data analysis to assess data structures and investigate integrity.
• Apply healthcare data models and standards (e.g., HL7 FHIR, OMOP), employing resources and mentors to ensure consistency.
• Accurately interpret, describe, convert, and integrate data from disparate, idiosyncratic, or custom data models into standardized formats.
• Ensure good data management practices for healthcare datasets intended for scientific use, maintaining data integrity, security, and HIPAA compliance.

Technical/Data Problem Solving & Expertise:

• Diagnose, troubleshoot, and resolve technical issues related to data systems to minimize disruptions, ensure data accuracy, and maintain system uptime.
• Stay current with and maintain knowledge of evolving healthcare data standards (e.g., HL7 FHIR, OMOP), models, and technologies, and drive their effective implementation.

Documentation & Communication:

• Create, produce, and maintain clear, concise, and accurate technical and standard business documentation for project processes, procedures, system designs, and solutions to facilitate clarity, reproducibility, and effective knowledge transfer. This includes process flow diagrams, workflow diagrams, sequence diagrams, state flow diagrams, and Entity-Relationship Diagrams (ERDs).
• Consistently and clearly communicate complex technical information to diverse audiences, including cross-functional teams, external stakeholders, customers, and senior leadership, managing expectations appropriately.
• Follow standard operating procedures for quality documentation, including developing business requirements, user stories, acceptance criteria, and system requirement specifications. Show sound professional judgment in employing, verifying, and editing AI content in documentation.
• Collaboration & Integration: Work closely and collaborate effectively with cross-functional teams and external stakeholders to ensure the seamless integration of healthcare data solutions.
• Operational Alignment: Work in alignment with global teams on Central European Time and U.S. Eastern Time.

Preferred Qualifications:

• Standards Mastery: Intermediate proficiency in the use of FHIR and other healthcare data standards.
• Coding Systems: Familiarity with healthcare coding systems (e.g., SNOMED, ICD, LOINC).
• Technical Skills: Practical experience with scripting languages (e.g., Python, R, SAS) and query languages (e.g., SQL) to deliver project outcomes.
• Certifications: Relevant certifications in healthcare informatics or healthcare data standards or technologies (e.g., FHIR certification).
• Domain Experience: Experience in human subjects research, clinical research, public health, or related fields.