Senior Data Scientist, Biomarker Analytics - Interventional Oncology

Key Skills

Aartificial intelligence, Clustering, Data science techniques, Effective communication skills, Google Cloud Platform (GCP), Machine learning techniques, Oncology, Python Programming, R Programming, RNA-seq Data processing

Job Description

As part of the Data Sciences team, the Senior Data Scientist will coordinate and analyze datasets including genomic, molecular, immunological, pathological, and imaging biomarkers to improve understanding of disease biology, enable patient selection strategies, and evaluate response in lung and other adjacent cancers. The successful candidate will apply statistical, machine learning, and AI approaches for analyses and interpretation of multi-modal biomarker datasets aligned to the therapeutic portfolio of INTO to help derive insights, progress the portfolio and develop new therapies for patients.

Key Responsibilities:

• Develop data analysis plans supporting analyses and reporting of biomarker readouts from clinical trials
• Analyze and interpret high-dimensional multi-modal biomarker datasets to drive decisions to progress the INTO portfolio
• Identify and integrate internal and publicly available data and resources to enable exploratory biomarker efforts
• Employ machine learning and AI models to help advance analytical capabilities
• Collaborate with discovery and translational sciences, clinical sciences, quantitative and data sciences as well as real-world evidence strategy teams to align and optimize analytical approaches
• Support the development of clinical biomarker data infrastructure that allows rapid and efficient use of biomarker data
• Effectively communicate analysis results to collaborators to drive decision-making

QUALIFICATIONS

• PhD. degree in Bioinformatics, Computational Biology, Biostatistics, or related field is required
• At least 2 years of work experience in bioinformatics projects is required. Work experience with clinicogenomics datasets is preferred
• Strong hands-on experience with multi-modal biomarker data (examples may include; RNA-seq, DNA-seq, TCR-seq, single-cell RNA-seq, and imaging datasets) is required
• Experience with statistical and machine learning methods such as survival analysis, regression analysis, dimensionality reduction, classification, and clustering is required
• Proficiency in using R/Python for the analysis of multi-omics data is required
• Experience in identification, acquisition, and analysis of publicly available genomic data such as The Cancer Genome Atlas (TCGA) is required
• Strong collaboration, interpersonal, and communication skills to clearly articulate problems, solutions, and concepts to a diverse team of scientists is required
• Proven track record of publications in top scientific journals and conferences is required
• Experience of analyzing oncology clinical data, preferably in lung cancer, is a plus
• Knowledge and experience of working to GCP principles in support of clinical studies is preferred
• Experience with cloud-based computing and analysis is preferred
• Experience with using generative AI models in health care applications is preferred
• This position can be located in Boston, MA; South San Francisco, CA; or New Brunswick, NJ, and may require up to approximately 10% travel.

Johnson & Johnson is an Affirmative Action and Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, age, national origin, or protected veteran status and will not be discriminated against on the basis of disability. The anticipated base pay range for this position is $113,000 to $195,500. For more information on how we support the whole health of our employees throughout their wellness, career and life journey, please visit www.careers.jnj.com .

https://www.careers.jnj.com/data-science