About the job :

Position Summary :

The Director Data & AI Delivery will lead end-to-end delivery of complex data, analytics, and AI/GenAI programs for global pharmaceutical clients. This role requires strong technical leadership, deep understanding of pharma data ecosystems, and proven experience in delivering scalable data platforms, digital solutions, and AI-driven products.

Job Responsibilities :

- Lead multi-disciplinary delivery teams across Data Engineering, AI/ML, MLOps, Product Engineering, Cloud, QA, and DevOps to deliver enterprise-grade pharma data products and AI solutions.

- Drive planning, estimation, roadmapping, risk management, and execution of large-scale programs using Agile/Scaled Agile practices.

- Ensure on-time, on-budget, and quality delivery for all engagements, with clear KPIs and governance dashboards.

- Manage BAU operations, SLAs, and incident/problem management for live data products and AI platforms.

- Engage with senior pharma stakeholders across R&D, Commercial, Medical, and Digital/Data functions to translate business needs into technical solutions.

- Build trusted relationships, influence decision-making, and provide thought leadership on Data & AI modernization.

Education :

- BE/B. Tech

- Master of Computer Application

Work Experience :

- 15 to 20 years of experience in technology delivery, with at least 8+ years in leading large data/AI programs.

- Strong experience delivering data platforms, AI/ML solutions, GenAI/LLM-based applications, or analytics systems for pharma or life sciences clients.

- Hands-on understanding of pharma datasets such as Sales & Marketing, Patient Data, Clinical Data, MDM, and Omnichannel data.

- Proven track record managing multi-million-dollar programs and multi-shore delivery teams.

- Experience with cloud platforms - Azure, data engineering (Databricks, PySpark), ML engineering, API development, and enterprise integration patterns.

- Experience with Agile/SAFe, product-based delivery models, and engineering governance.

Behavioral Competencies :

- Teamwork & Leadership

- Motivation to Learn and Grow

- Ownership

- Cultural Fit

- Talent Management

Technical Competencies :

- Problem Solving

- Lifescience Knowledge

- Communication

- Project Management

- Attention to P&L Impact

- Capability Building / Thought Leadership

- Scale of revenues managed / delivered