Director - Data Strategy & AI Transformation (AI)

Location: Berkeley Heights, New Jersey, United States

Salary: $157,600–$205,425 annually

Company

hirify.global provides data, analytics, AI, and commercial transformation consulting services to Life Sciences organizations.

What you will do

• Advise pharmaceutical, biotechnology, and medical device clients on enterprise data, analytics, and AI transformation.
• Develop data and AI roadmaps aligned with commercial, medical, patient services, and market access objectives.
• Lead modernization of enterprise data ecosystems using cloud platforms, scalable architecture, governance, integration, and master data initiatives.
• Identify and operationalize AI, Generative AI, machine learning, and advanced analytics use cases.
• Lead strategic engagements from discovery through execution and present recommendations to executive and C-suite stakeholders.
• Support business development, reusable accelerators, thought leadership, and cross-functional global team leadership.

Requirements

• 15+ years of experience in data strategy, data management, analytics, or data transformation consulting.
• Experience serving pharmaceutical, biotechnology, or medical device clients.
• Experience leading enterprise-level data modernization initiatives.
• Strong understanding of cloud-based data ecosystems and modern data architecture, including Azure and/or AWS.
• Experience with Snowflake, Databricks, or comparable cloud data platforms.
• Ability to engage executive stakeholders and translate business objectives into data transformation strategies.

Nice to have

• Management consulting experience with a recognized consulting organization.
• Experience supporting AI and Generative AI transformation initiatives.
• Knowledge of Life Sciences commercial data, customer data, patient data, MDM, governance, data quality, and analytics ecosystems.
• Experience with large-scale enterprise data programs and multimillion-dollar budgets.

Culture & Benefits

• Leadership across global, cross-functional teams spanning strategy, engineering, analytics, and delivery.
• Focus on innovation, collaboration, continuous learning, and capability building.
• Opportunity to develop reusable frameworks and differentiated Data, AI, and Commercial Transformation offerings.