Associate Principal Scientist, Bioinformatics, Immuno-Oncology Analytics

Job Description

The Translational Genome Analytics group within the Data, AI & Genome Sciences Department is recruiting an Associate Principal Scientist to join our data science team. We are seeking an experienced and innovative computational scientist to perform data mining of multi-modal genome-scale molecular data and inform decisions across all stages of our company’s expanding oncology pipeline. The successful candidate will:

• Enable reverse translation from clinical datasets to inform biomarker discovery, combination strategies, and novel target identification in molecularly defined patient populations with high unmet medical need.

• Analyze, summarize and visualize the findings from large multi-modal clinico-genomic datasets which include bulk RNAseq, WES/WGS, epigenetic profiling, single-cell RNAseq, and proteomics data from oncology clinical trials and real-world datasets.

• Leverage advanced analytical methods and multivariate predictive modeling to define molecular subtypes of patients with distinct composition of Tumor Micro Environment, molecular drivers and clinical outcomes.

• Effectively present data analyses to inform and interact with stakeholders representing a wide span of internal organizations, including early discovery, translational and clinical development teams.

Education Minimum Requirement:

• PhD in quantitative discipline such as Engineering, Applied Physics/Mathematics, Bioinformatics, Computational Biology or related field with a significant computational and statistical component.

Required Experience and Skills:

• At least 3 years post-PhD experience in applying computational methods in cancer biology in a pharma, biotech or academic setting

• Some combination of the below skills:

- Demonstrated expertise in the application of methods of statistical learning and data mining to the integrative analysis of multimodal, high-dimensional molecular profiling datasets in the oncology and immuno-oncology context 

- Hands-on analysis experience with algorithms for large genetic, genomic, immunogenomic and clinical datasets (e.g. IEDB, TCGA, GTEx, DepMap)

- Extensive experience and demonstrated expertise to code in scientific computation environments (R/Python, Matlab) with adoption of best practices for reproducible data analyses.

• 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:

• Demonstrated experience with analysis of genome-scale genomic data originating from clinical trials.

• Deep understanding of the major concepts of cancer biology as represented in multi-modal molecular data.

• Experience within a matrixed industry environment and ability to effectively collaborate with colleagues from a wide range of disciplines.

• Record of publishing in high profile scientific journals.

As an Equal Employment Opportunity Employer, we provide equal opportunities to all employees and applicants for employment and prohibit discrimination on the basis of race, color, age, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, disability status, or other applicable legally protected characteristics.  As a federal contractor, we comply with all affirmative action requirements for protected veterans and individuals with disabilities.  For more information about personal rights under the U.S. Equal Opportunity Employment laws, visit:

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We are proud to be a company that embraces the value of bringing together, talented, and committed people with diverse experiences, perspectives, skills and backgrounds. The fastest way to breakthrough innovation is when people with diverse ideas, broad experiences, backgrounds, and skills come together in an inclusive environment. We encourage our colleagues to respectfully challenge one another’s thinking and approach problems collectively.