Analytic Consultant, IHD Support

About the role

The Analytic Consultant, IHD Support plays a key role in helping clients successfully leverage Instant Health Data (IHD), a next-generation healthcare data analytics platform designed to improve the quality and efficiency of medical research.

Responsibilities

• Build expertise in the features, benefits, and applications of the Instant Health Data (IHD) platform and new products.
• Become proficient with a variety of large, complicated healthcare datasets.
• Collaborate with clients to understand project requirements and objectives related to health data analysis and provide guidance around implementation in IHD.
• Establish a relationship with and provide ongoing support to clients, addressing queries and offering guidance in leveraging data insights effectively.
• Develop and present technical trainings, 1-on-1, or small group working sessions with IHD users.
• Prepare training materials and documentation for both internal and external audiences.
• Collaborate with cross-functional teams on operational processes and client support initiatives, contributing insights from client interactions to support the successful rollout and adoption of new platform features.
• Support quality control and protocol development for internal and external research projects, ensuring project outputs align with defined objectives.

Requirements

• Bachelor's or Master's degree in a related field (e.g., Health Informatics, Biostatistics, Epidemiology, Public Health, or a related discipline).
• 2–4 years of relevant experience in outcomes research, health economics, epidemiology, life sciences consulting, analytics, or an academic research setting.
• Strong understanding of and experience working with healthcare data and/or real-world data (RWD), such as claims, EHR, hospital, registry data, etc.
• Demonstrated analytical, organizational, and creative problem solving with the ability to interpret complex data sets and generate meaningful insights.
• Experience in utilizing statistical methods for data analysis.
• Proficiency in statistical software, such as R or Python, is a plus.
• Clear, confident communication and presentation skills with the ability to translate technical concepts for non-technical audiences; prior client-facing or customer support experience is a plus.
• Demonstrated ability to manage multiple priorities, meet deadlines, and contribute effectively within a collaborative team environment.