Head of Information Technology

Job Title: Head of IT (Director Level)

Location: Shanghai

Position Overview

As the strategic owner of the company's technology foundation, you will lead the IT function to power innovation across the organization. Your core mission is to build, secure, and operate a robust, scalable, and compliant technology platform that enables business operations and accelerates scientific discovery. A critical component of this role is serving as the primary technology partner and enabler for the Data Science & AI function. You will be responsible for providing the cutting-edge infrastructure, integrated data pipelines, and production-grade platforms that allow our data scientists and AI researchers to focus on model development and scientific insight. This role is pivotal in turning data into a strategic asset.

Key Responsibilities

• Strategic Leadership & Planning
• Develop and execute the corporate IT strategy and roadmap, ensuring alignment with business objectives and the strategic needs of the R&D organization, including Data Science & AI.
• Own the enterprise technology architecture, ensuring it is secure, scalable, and cost-effective.
• Manage the IT budget, making strategic investments in foundational capabilities that benefit the entire enterprise, with particular consideration for computational and data needs.
• Primary Enabler for Data Science & AI
• Infrastructure as a Service: Provide and manage the High-Performance Computing (HPC) and GPU-accelerated compute environment (cloud or hybrid) required for large-scale data processing and AI model training.
• Platform Engineering: Build and maintain the enterprise data platform and pipeline infrastructure that ingests, cleanses, and consolidates data from diverse sources (lab systems, clinical trials, external data) into a consumable state for analytics and AI.
• Data Governance & Security: Implement the technical controls, data governance tools, and security frameworks (access management, encryption) that protect sensitive R&D and clinical data assets, in partnership with Data Science & AI and Legal/Compliance.
• Enterprise Systems, Security & Compliance
• Lead the strategy, implementation, and integration of core enterprise systems (ERP, CRM) and R&D-specific applications (e.g., ELN, LIMS, CTMS).
• Be ultimately responsible for corporate cybersecurity, risk management, and disaster recovery. Ensure all systems and data practices meet GxP, SOX, GDPR, and other relevant regulations.

• Drive the strategy for cloud adoption, SaaS management, and vendor partnerships.

• Team & Operational Excellence

• Lead the IT organization, fostering a culture of service, engineering excellence, and business partnership.
• Establish and measure against SLAs for IT service delivery, ensuring high reliability and user satisfaction.
• Manage key vendor relationships and technology partnerships.3. Qualifications & Experience

Education & Experience

• Bachelor's degree or higher in Computer Science, Bioinformatics, Computational Chemistry, or a related field.
• Minimum of 10 years of progressive IT leadership experience, with at least 3 years in a dedicated IT leadership role within the biopharma, MedTech, or life sciences industry.
• Must have direct, hands-on experience successfully supporting Data Science/AI teams or projects, such as building data platforms, HPC environments, or MLOps pipelines.
• Familiarity with the end-to-end drug development process (target identification, lead optimization, pre-clinical, clinical) is a strong plus.
• Technical Mastery: Deep expertise in cloud computing (IaaS/PaaS), enterprise data architecture, and information security. Must possess a solid understanding of the technology stack required for AI-driven R&D (e.g., containerization/Docker/K8s, workflow engines, model serving).
• Domain Knowledge: Familiarity with common life sciences systems (e.g., ELN, LIMS, CDMS, SDMS) and their data standards. Understanding of GxP compliance and Computerized System Validation (CSV) requirements.
• Data Acumen: Strong data mindset with an appreciation for the critical role of data governance in R&D. Experience managing large-scale scientific data.