Director Information Systems – AI & Data

Ligand Pharmaceutical•San Diego, CA

11d•$220,000 - $265,000

About The Position

Ligand Pharmaceuticals is seeking a Director Information Systems – AI & Data to lead the company’s information systems, data, analytics, and artificial intelligence strategy and execution. Reporting to the CFO, this leader will translate business needs into secure, scalable technology and data solutions that improve productivity, decision-making, risk management, and long-term value creation. The role works with senior leaders and functional teams to prioritize investments, strengthen governance, drive adoption, and measure business impact. The position may be based in San Diego, California, or Boston, Massachusetts. The Director will develop an integrated technology, data, analytics, and AI strategy; lead AI, automation, and analytics initiatives from business case through implementation and scale; and establish responsible AI practices, data governance, and scalable data architecture. The role also leads or supports enterprise platform selection and optimization, coordinates with infrastructure and cybersecurity partners, and oversees technology risk and compliance activities. Responsibilities include building internal and external capabilities, managing budgets and vendors, and communicating plans, risks, and outcomes to senior leadership. Ligand is a biopharmaceutical company that develops or acquires technologies to help pharmaceutical companies develop medicines. Its business model centers on royalty-generating assets, partnerships with pharmaceutical and biotechnology companies, and diversified royalty revenue. The company describes its culture as entrepreneurial, analytical, collaborative, and focused on initiative, independent thinking, and outcomes. Its mission includes funding and investing in medicines for severe and life-threatening diseases. The expected salary range is $220,000–$265,000. Actual pay depends on experience, qualifications, geographic location, and other job-related factors. Compensation includes an annual incentive bonus and a generous equity package. Benefits include a flexible work schedule, medical, dental, and vision coverage, short- and long-term disability and life insurance, a 401(k) match, stock options, bonus, and paid time leave. New hires must complete background and reference checks, and candidates must be legally authorized to work in the United States without sponsorship.

Requirements

12+ years of progressive experience in information systems, data, analytics, AI, or related technology roles.
At least 7 years in leadership positions.
Bachelor’s degree in a relevant field required.
Demonstrated experience designing and implementing enterprise-scale data solutions, AI applications, automation, and modern cloud-based platforms such as Azure or AWS.
Deep working knowledge of data strategy, architecture, engineering, governance, advanced analytics, data modeling, integration, database management, and data security.
Recent hands-on leadership of AI implementation, including generative AI, machine learning, large language models, or intelligent automation.
Experience introducing new technology capabilities through structured change management, adoption planning, training, and measurement.
Ability to influence across functions, simplify complex issues, make sound decisions, and communicate effectively with senior leaders and technical teams.
Strong vendor, budget, program, and team leadership capabilities.
Legally authorized to work in the United States without sponsorship.
Successful completion of a background and reference check.

Nice To Haves

Advanced degree.
Experience building an internal AI assistant or similar enterprise tool.
Experience in life sciences and familiarity with regulated functions such as quality, regulatory, compliance, and FDA-related requirements.

Responsibilities

Develop and execute an integrated information systems, data, analytics, and AI strategy aligned with business priorities and growth objectives.
Advise senior leadership on technology investments, enterprise platforms, automation, analytics, emerging technologies, and related risks.
Partner with business leaders to identify, prioritize, and deliver practical solutions with measurable operational and financial impact.
Lead AI, automation, and analytics initiatives from business case and pilot through implementation, adoption, monitoring, and scale.
Establish responsible AI practices covering model development, security, privacy, legal review, governance, and appropriate use.
Build organizational capability and adoption through change management, training, and user-centered implementation.
Define and report metrics for adoption, performance, return on investment, and business outcomes.
Establish data governance standards for quality, classification, ownership, access, lineage, metadata, retention, security, and compliance.
Assess the current data and analytics environment and define a scalable target architecture supporting reporting, advanced analytics, and AI.
Oversee data models, integration patterns, data pipelines, storage solutions, and data products to ensure reliable and efficient access to information.
Advance self-service reporting and analytics while maintaining appropriate controls and data integrity.
Lead or support selection, implementation, integration, optimization, and adoption of enterprise platforms across relevant business functions.
Partner with infrastructure, cybersecurity, and enterprise architecture resources to ensure solutions are secure, resilient, interoperable, and aligned with technology standards.
Oversee monitoring, availability, performance, and continuous improvement for data and AI platforms.
Oversee or coordinate technology risk, cybersecurity, data protection, business continuity, disaster recovery, and incident response activities.
Ensure technology, data, and AI practices support applicable privacy, regulatory, quality, and compliance requirements, including life sciences requirements.
Support technology and cybersecurity due diligence for investments, acquisitions, portfolio companies, and new business initiatives.
Build and lead internal and external capabilities across AI, data governance, architecture, engineering, business intelligence, enterprise systems, and support.
Develop and manage budgets, roadmaps, resource plans, and delivery priorities for technology, data, and AI initiatives.
Manage vendor strategy, due diligence, contracting, performance, service levels, and cost effectiveness.
Communicate strategy, progress, risks, recommendations, and results clearly to senior leadership and business stakeholders.