Job Description
The Translational Genome Analytics group within the Data, AI & Genome Sciences Department is recruiting a Director of Oncology Biomarker Discovery to join an oncology data science team dedicated to advancing our company's vast and expanding oncology pipeline, with a focus on multimodal biomarker discovery, validation, and implementation.
The successful candidate will:
- Investigate proprietary and public real-world molecular datasets and clinical trials in conjunction with tissue and periphery assays with a goal of identifying robust multimodal biomarkers of response and resistance to an array of cancer therapies across indications and lines of therapy, with line of sight to diagnostic development.
- Leverage advanced AI/ML approaches to integrate multi-modal data including RNAseq, WES, ctDNA, digital pathology, proteomics, immune activation assays, and liquid biopsies to discover biomarkers and molecularly defined groups of patients as well as molecular mechanisms of modulation of therapeutic response reflected in longitudinal analytes.
- Effectively present data analyses to inform and interact with stakeholders representing a wide span of internal organizations, including Translational Oncology, Molecular Diagnostics, Clinical Development, Statistics, Therapeutic Area Biology, and Commercial Development.
QUALIFICATIONS:
Education:
- Master's (with 12+ years) or Ph.D. (with 8+ years) in Engineering, Applied Mathematics, Bioinformatics, Computational Biology or related field with a significant computational and statistical expertise and relevant experience in a pharma, biotech or academic setting.
Required Experience and Skills:
- Extensive experience applying computational methods in cancer biology.
- Extensive experience and demonstrated expertise with scientific cloud-based computation environments (R/Python highly preferred).
- AI/ML exposure and experience including supervised and unsupervised machine learning, foundation models, and modern coding.
- Experience with genomic datasets across cancer types and therapeutic modalities with proven expertise in drug development pipeline impact.
- Hands-on analysis experience with algorithms for large genetic, genomic, immunogenomic and clinical datasets (e.g. TCGA, GTEx, DepMap, CPTAC) as well as RWD genomic, imaging and EHR datasets.
- Experience with leading a team of highly performing computational scientists.
- Strong communication and presentation skills; ability to guide and influence decisions through use of data-driven hypotheses; attention to detail;
- Independent, flexible and collaborative mindset.
Preferred Experience and Skills:
- Proven experience with analysis of genomic data originating from clinical trials.
- Exposure and experience with companion diagnostic development, preferably for NGS.
- Understanding of the major concepts of cancer biology as represented in molecular data.
- Expert knowledge of methods of statistical learning and data mining and application to biological problems.
- Experience with a matrix environment and ability to effectively collaborate with colleagues from a wide range of disciplines.
- Record of publishing in high profile scientific journals.
#EligibleforERP
Required Skills:
- Artificial Intelligence (AI)
- Cancer Genomics
- Cancer Research
- Cloud Computing
- Computational Methods
- Data Science
- Genomic Data Analysis
- Machine Learning (ML)
- Multimodal
- Multimodal Analysis
- Oncology
Preferred Skills:
