Director, Data Science & AI, Scientific Lead

Job Description

Our Artificial Intelligence and Machine Learning (AI/ML) capabilities are vital catalysts for our mission to invent new medicines that save and enhance lives. The Data, AI, and Genome Sciences (DAGS) function at our organization adopts an AI/ML-first approach to enhance target and biomarker discovery by driving the understanding of complex disease mechanisms.

As the Director of Data Science and AI, Scientific Lead, you will leverage your expertise in genomic technologies, multi-omics data integration, and disease biology to drive the development of multi-modal AI/ML modeling approaches, biological validation and insight generation for target and biomarker discovery. You will collaborate with Biologists, Computational Biologists, Data Scientists, Software Engineers, and AI/ML Scientists and Engineers as part of a cross-functional team dedicated to identifying therapeutic targets. You will report to the Executive Director and Head of AI/ML.

Primary Responsibilities:

• Drive the evaluation of cutting-edge, scalable data science and machine learning approaches to integrate multi-omics data and decode disease biology to drive novel target and biomarker discovery.

• Guide the development and validation of advanced AI/ML approaches leveraging high-throughput, deep-profiling and patient-derived tissue data to decode disease-relevant cellular interaction and cell-type specific molecular networks with the goal of novel target and biomarker discovery.

• Drive data strategy for foundation dataset for Foundation Models for disease biology discovery, collaborating with cross-functional teams to understand project goals and data requirements.

• Serve as a subject matter expert to AI/ML Scientists and Engineers, providing scientific oversight over multi-modal data integration and cutting-edge AI/ML model validation across several therapeutic areas.

• Clearly communicate results to project teams, our company’s scientific community, and the external scientific community through internal documents, presentations, and publications in leading journals.

Required Experience and Skills:

• PhD in a relevant field such as computational biology, bioinformatics, systems biology, or a related discipline, with 8+ years of experience in genomic technologies, multi-omics analysis, therapeutics sciences, and disease biology OR MS in above fields and 10+ years of relevant experience.

• Strong understanding of multi-omics data, including analysis techniques, algorithms, statistical approaches, multi-omics data integration, and relevant tools.

• Demonstrated expertise in decoding disease biology by leveraging advanced machine learning and statistical inference frameworks to analyze multi-modal (transcriptomics, epigenomic) and multi-scale (single cell and/or spatial) patient-derived data.

• Experience in applying state-of-the-art analytical approaches to leverage preclinical functional genomics approaches and high-throughput screens.

• Expertise in Python and best practices for reproducible data analysis.

• Excellent communication skills and ability to work collaboratively in a multi-disciplinary team.

Preferred Experience & Skills

• Hands-on experience with omics data generation is a plus.

• Experience with Knowledge Graphs, including graph databases and query languages, would be advantageous.

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