Executive Director, Data, AI & Collaboration Services

About Us 

Position Title: Executive Director, Data, AI & Collaboration Services 

Department: Information Technology 

Reports To: VP, Head of IT 

Location: South San Francisco, CA (preferred) or Princeton, NJ – On-site 4 days per week (Mon to Thurs) 

Job Overview 

The Executive Director, Data Strategy, AI & Collaboration is a pivotal role that will define and drive Kardigan's approach to harnessing data, artificial intelligence, and modern collaboration technologies as strategic assets across the enterprise. This leader will own the end-to-end roadmap for these interconnected domains — with a deliberate emphasis on Data and AI — while ensuring that collaboration platforms amplify the effectiveness of scientific, clinical, and business teams. 

Operating within IT alongside peers in IT Operations and Solution Delivery, this individual will serve as the company's foremost internal expert and thought leader on data-driven decision-making and AI-enabled innovation. They will work at the intersection of technology, science, and business strategy — translating ambition into concrete, measurable capabilities. The role demands both visionary leadership and a willingness to roll up one's sleeves: building programs from the ground up, influencing without large teams, and delivering lasting impact in a resource-efficient model. 

This is a rare opportunity for a technically deep, strategically minded leader to shape the data and AI foundation of a company where every decision ultimately serves patients. 

Essential Duties and Responsibilities 

• Data Strategy, Implementation & Governance 
  • Develop and own the enterprise data strategy, roadmap, and governance framework, ensuring data is treated as a first-class strategic asset across all  corporate functions (e.g. R&D, G&A, and Commercial & Medical) 
  • Architect and implement a scalable, cloud-native data platform — including data lake, data warehouse, and data mesh components — that enables self-service analytics and supports both structured and unstructured scientific data 
  • Establish enterprise-wide data standards, ontologies, master data management (MDM) practices, and metadata management to drive data quality, lineage, and discoverability 
  • Define and enforce data governance policies, access controls, and stewardship programs in compliance with FDA 21 CFR Part 11, ICH E6(R2), GDPR, HIPAA, and other applicable regulatory frameworks 
  • Partner with Legal, Regulatory Affairs and Quality to ensure data integrity requirements are embedded by design into all data platforms and pipelines 
  • Build the organizational capabilities — processes, roles, tools, and culture — needed to sustain data excellence as the company grows 

• Artificial Intelligence Strategy & Implementation 
  • Lead the development and execution of a comprehensive AI strategy that identifies, prioritizes, and delivers measurable value across the organization 
  • Establish the company's AI/ML platform, including infrastructure for model development, validation, deployment, monitoring, and retraining, leveraging cloud-native services 
  • Drive the responsible adoption of Generative AI — including large language models (LLMs) and multimodal models — for use cases such as scientific literature synthesis, regulatory document drafting, clinical data exploration, and internal knowledge management 
  • Build and maintain an AI governance framework encompassing model validation, explainability, bias detection, human oversight requirements, and alignment with FDA AI/ML guidance and the EU AI Act 
  • Identify and manage strategic partnerships with AI vendors and technology providers to accelerate capability development  
  • Champion a culture of data literacy and AI fluency across business and scientific functions; develop internal training programs and communities of practice 
  • Stay ahead of the rapidly evolving AI landscape — evaluating emerging technologies and providing executive-level counsel on when and how to adopt 

• Collaboration Tools  
  • Own the strategy, architecture, and roadmap for enterprise collaboration platforms — including Microsoft 365 / Teams, SharePoint Online — with a focus on enabling seamless, compliant collaboration across internal teams and external partners 
  • Drive platform consolidation, rationalization, and integration to reduce fragmentation and improve the employee experience 
  • Lead change management and adoption programs, working closely with functional leaders to maximize the value of collaboration investments 

• Executive Leadership & Organizational Impact 
  • Serve as a trusted strategic advisor to the VP, Head of IT, and functional leaders on data, AI, and digital innovation topics; regularly present roadmaps, business cases, and progress to senior leadership and the board as appropriate 
  • Build, lead, and develop a high-performing team; leverage a hybrid model of employees, managed service providers, and strategic partners to maximize impact with efficient resource utilization 
  • Define OKRs, KPIs, and value metrics for the Data, AI & Collaboration portfolio; establish reporting cadences and accountability mechanisms to track delivery and business impact 
  • Own the budget, vendor relationships, and contract governance for the portfolio; negotiate enterprise agreements with technology and service providers 
  • Collaborate closely with IT Operations and Solution Delivery peers to ensure architectural coherence, cybersecurity alignment, and integration across the IT landscape 
  • Represent Kardigan in external forums, industry consortia, and regulatory advisory groups as a voice for responsible, innovation-forward use of data and AI in life sciences 

Qualifications and Preferred Skills 

• Education 
  • Bachelor's degree required in Computer Science, Data Science, Bioinformatics, Engineering, or a related quantitative discipline 
  • Advanced degree (M.S., Ph.D., or MBA) strongly preferred 

• Required Experience 
  • 12+ years of progressive experience in data, analytics, or technology leadership, with a minimum of 5 years at the Director level or above in a life science, biotechnology, pharmaceutical, or medical device company 
  • Demonstrated track record of building and executing enterprise data strategy and governance programs in a GxP-regulated environment, including firsthand knowledge of FDA 21 CFR Part 11, ICH E6(R2), and data integrity principles 
  • Proven experience architecting and delivering cloud-based data platforms at scale — hands-on proficiency with at least one major platform (e.g. Snowflake, Databricks, Azure Synapse, AWS, or GCP equivalent) 
  • Direct experience implementing AI and machine learning solutions in a life sciences context, including model validation, documentation, and governance in a regulated setting 
  • Deep familiarity with the Microsoft 365 ecosystem and enterprise collaboration platforms  
  • Track record of operating effectively in fast-paced, lean, resource-constrained organizations; comfortable as a builder and an operator simultaneously 
  • Demonstrated executive presence and ability to influence C-suite, board members, and cross-functional senior stakeholders 

• Strongly Preferred Experience 
  • Experience with clinical data standards (CDISC, SDTM, ADaM) and integration of clinical trial data into enterprise analytics platforms 
  • Hands-on familiarity with generative AI platforms (Azure OpenAI Service, AWS Bedrock, Anthropic Claude API) and validated deployment in a regulated environment 
  • Knowledge of Veeva Vault (eTMF, RIM, QualityDocs), CTMS, LIMS, or ELN systems and their data integration patterns 
  • Experience with real-world data (RWD) and real-world evidence (RWE) platforms and their applications in drug development and commercial strategy 
  • Exposure to federated data architectures, data mesh, or data fabric patterns in a multi-site or multi-partner setting 
  • Familiarity with emerging AI regulatory frameworks including FDA's AI/ML-Based Software as a Medical Device (SaMD) guidance and the EU AI Act 
  • Prior experience in a company scaling from clinical stage through commercial launch 

• Core Competencies 
  • Strategic vision paired with operational execution — the rare ability to set direction and get things done 
  • Deep technical depth in data engineering, ML/AI, and cloud architecture; credible with both engineers and scientists 
  • Exceptional communication and storytelling skills; able to translate technical complexity into compelling executive narratives 
  • Entrepreneurial mindset with high tolerance for ambiguity and a bias for action 
  • Collaborative leadership style; builds trust quickly across diverse functions and seniority levels 
  • Strong business acumen — understands how data and AI investments connect to pipeline value, competitive differentiation, and patient outcomes 
  • Unwavering commitment to responsible AI, data ethics, patient privacy, and regulatory compliance