Director, Head of Bioinformatics for Immunology

Role Summary

The role of Director, Head of Bioinformatics for Immunology in Quantitative Medicine and Genomics (QM&G) is pivotal for driving data-driven insight for target identification and validation, biomarker discovery, clinical development, forward and reverse translation, therapeutic innovation, and manufacturing within the QM&G functional area and across R&D. This role is responsible for leading a distributed team that leverages cutting-edge bioinformatics to derive novel insights for end-to-end drug discovery and development; while the position is focused primarily in Immunology there are also opportunities for cross-collaboration in multiple therapeutic areas, including, Aesthetics, Specialty Medicine, Biotherapeutics, Manufacturing Science and Technology.

Responsibilities

• Accelerate AbbVie‚Äôs drug discovery and development pipeline by establishing forward-thinking informatics strategies and executing on results for multiple disease areas within Immunology
• Lead a dynamic team of bioinformaticians, and data scientists. Foster a culture of high performance and professional growth, ensuring the team operates at the cutting-edge of scientific research and development.
• Spearhead innovative computational systems biology initiatives to revolutionize the discovery of therapeutic targets. Integrate insights from genetic, multi-omics, and functional genomics data to drive innovation in therapy development.
• Oversee the application of AI/ML methods in both Discovery and clinical Development. Enable reverse translation leveraging cross-sectional, multi-modal clinical data analysis and method development.
• Optimize genetic medicine and biotherapeutics manufacturing capabilities through advanced computational insights and AI/ML applications, enhancing the efficacy and scalability of the next-generation therapeutic approaches.
• Foster strong collaborations within the Bioinformatics community and across R&D, clinical teams, and other departments to ensure bioinformatic and genetic insights are effectively integrated into AbbVie's pipeline programs.
• Cultivate and lead partnerships with academic institutions, biotechnology companies, and technology providers. Drive the evaluation and integration of emerging technologies and methodologies, enhancing team capabilities and keeping AbbVie at the helm of scientific progress.

Qualifications

• PhD in bioinformatics, statistics, mathematics, computer science, computational biology, genomics, or a related field with 8+ years industry/academic experience
• Or master‚Äôs degree with 15+ years of relevant experience
• Proven success of managing, leading, and mentoring interdisciplinary teams in large-scale research environments, demonstrating exceptional management and leadership capabilities
• Extensive experience applying AI/ML techniques in drug discovery and development to drive innovation and therapeutic outcomes, with proven results and impact
• Deep expertise in transcriptomics and proteomics, encompassing bulk, single-cell, and spatial approaches, and multi-omic integration methodologies
• Proficient in genetic analysis techniques, including GWAS, QTL, genetic risk modeling, and multi-omics integration, with a focus on actionable insights
• Strong background in target identification, biomarker discovery, and clinical translation, aimed at enhancing therapeutic development processes
• Demonstrated ability to collaborate cross-functionally, with experience in working with clinical teams and translating complex computational findings into clinical insights for diverse teams
• Adept at articulating complex scientific concepts to non-scientific stakeholders and executive leadership, ensuring clarity and strategic alignment

Skills

• AI/ML techniques in drug discovery and development
• Bioinformatics, systems biology, and multi-omics integration
• Genetic analysis: GWAS, QTL, genetic risk modeling
• Transcriptomics, proteomics (bulk, single-cell, spatial)
• Target identification and biomarker discovery
• Clinical translation and cross-functional collaboration
• Effective communication with non-scientific stakeholders and leadership

Education

• PhD in bioinformatics, statistics, mathematics, computer science, computational biology, genomics, or related field (8+ years of industry/academic experience) OR
• Master‚Äôs degree with 15+ years of relevant experience