Bristol-Myers Squibb Company

Senior Research Investigator, Late Stage Translational Bioinformatics Oncology

Location
Princeton, NJ, United States
Posted
Jun 24, 2019
Ref
R1515368
Required Education
Doctorate/PHD/MD
Position Type
Full time
We are seeking a talented and motivated bioinformatics scientist to join our Late Stage Translational Bioinformatics Oncology team within the Translational Bioinformatics group at Bristol-Myers Squibb (BMS). This team is responsible for applying cutting-edge bioinformatics, statistics, and data-mining methods; working with clinical and large-scale omics data sets from BMS's industry-leading late stage oncology/immuno-oncology (I-O) pipeline; influencing development strategies and maximizing the value of BMS's portfolio. This team of bioinformatics scientists also has the exciting opportunity to make major contributions to the scientific knowledge of cancer biology and to the improvement of treatment for cancer patients.

Responsibilities

Engage late stage clinical development teams, biomarker scientists, biostatisticians and others key stakeholders to define and execute biomarker data analysis plans for late stage oncology clinical studies

Perform analysis of clinical and biomarker datasets (e.g., large-scale omics datasets including RNASeq, exome and whole genome sequencing, single cell sequencing) and derive clinically meaningful interpretations

Identify potential biomarkers for patient enrichment strategies and gain mechanistic insights of responses and resistances to I-O treatments

Summarize analysis results and report conclusions to BMS decision-making bodies; help communicate conclusions to regulatory agencies and the broad scientific community

Evaluate and adapt latest scientific findings and methods into bioinformatics analysis plans

Qualifications

Ph.D. in bioinformatics, statistics, biological or physical science with 5+ years of industry experience

Demonstrated experience working with clinical study data is required; familiar with late stage clinical development process

Deep understanding of disease biology in immuno-oncology is a strong plus

Ability to work both independently and collaboratively, and to handle several concurrent, fast-paced projects while conforming with rigorous requirements of clinical studies

Broad experience with data generated by one or more high-throughput molecular assays: next-generation sequencing, flow cytometry, mass spectrometry proteomics, etc.

Strong experience using high-level programming languages such as R, MATLAB, Python or Perl for complex data analysis and reproducible research practices

Strong problem-solving and collaboration skills, as well as rigorous and creative thinking

Excellent communication, data presentation and visualization skills

Capable of establishing strong working relationships across the organization