Senior Data and AI Analyst

Senior Data and AI Analyst, Investor Relations

Position Summary

The Senior Data and AI Analyst plays a critical role in advancing IREC’s investor relations consulting practice, which advises biotechnology and healthcare companies on IR strategy in partnership with executive leadership and corporate communications teams. This role is responsible for the sourcing, management, analysis, and interpretation of complex investment and market data used to support client engagement and research initiatives.

In this role, the Senior Data and AI Analyst oversees core data systems and processes while leveraging advanced analytics and AI-enabled tools to generate actionable insights, identify trends, and improve the efficiency, consistency, and quality of data-driven outputs. The position serves as an important shared resource to client teams – helping to deliver high-quality, data-driven counsel to clients. In addition to hands-on analytical work, the Senior Data and AI Analyst serves as a leader in responsible AI adoption—designing scalable, compliant workflows that combine human expertise with AI to accelerate research, enhance thought leadership, and strengthen client-facing materials. The role requires close collaboration with internal teams, external vendors, and enterprise partners, and serves as a representative of IREC within the broader parent organization, contributing to firmwide data and innovation initiatives.

Senior Data and AI Analysts demonstrate strong attention to detail, sound judgment, curiosity, and an entrepreneurial mindset, as well as leadership in guiding teams through evolving data, technology, and analytical capabilities.

Essential Functions

Analytics, Research & Insight Development

• Conduct sophisticated quantitative and qualitative analysis of investment, market, and peer data to support Investor Relations strategy, internal planning, and client engagement
• Leverage AI-enabled analytic tools to accelerate data exploration, pattern recognition, trend analysis, and benchmarking—while applying expert judgment and validation to all outputs
• Conceptualize and execute data-driven research to support firm thought leadership, executive briefings, and client deliverables
• Translate complex datasets into clear, accessible insights, moving beyond raw data to explain implications, risks, and opportunities
• Deliver recurring and ad-hoc reporting (e.g., bi-weekly, monthly, quarterly), standardizing outputs to promote consistency and ease of consumption across teams
• Conduct market research on emerging trends in Generative AI, digital platforms, and healthcare communications
• Summarize findings, develop brief reports, and surface insights to support strategic discussions and planning
• Monitor competitive activity, new tools, and industry developments relevant to medical education and technology

Data Strategy, Management & Governance

• Oversee and manage IREC’s databases, data subscriptions, and internal resources, ensuring accuracy, completeness, consistency, and appropriate access
• Design scalable, repeatable data management and data entry processes that can be implemented consistently across teams
• Review, audit, and standardize raw investment data received in multiple formats, using both traditional and AI-assisted techniques to improve timeliness and data quality
• Manage database licenses, vendor relationships, and coordination with Precision AQ partners to ensure optimal configuration and compliant use
• Audit CRM systems and datasets to identify and remediate duplicate, incomplete, or inconsistent records
• Evaluate new data tools, platforms, and datasets—assessing value, usability, security, and alignment with business and regulatory needs

AI Enablement, Governance & Applied Innovation

• Integrate AI responsibly into data workflows, research processes, and reporting—using AI to enhance speed, consistency, and insight generation while preserving human accountability
• Serve as the subject matter expert on Precision AQ AI policy, governance standards, data privacy requirements, and acceptable-use guidelines
• Design and document AI-supported workflows, including prompt frameworks, templates, and quality-control checkpoints for i