Senior Scientist - Heme/Onc - Translational IPS

$109,000 - $150,700/Yr

Bristol-Myers Squibb - Summit, NJ

Full-time - Senior

Hybrid - Summit, NJ

Chemical Manufacturing

About the position

The Senior Scientist in Heme/Onc - Translational IPS at Bristol Myers Squibb is a key role focused on leveraging computational methods to analyze high-dimensional molecular profiling data. This position aims to drive transformative insights for patient benefit by collaborating with scientific and clinical experts to influence drug discovery and development strategies in hematology and oncology. The role involves applying advanced bioinformatics, statistics, and machine learning techniques to derive clinically meaningful interpretations from complex datasets, ultimately impacting the treatment of cancer patients.

Responsibilities

• Apply computational methods to molecular profiling datasets and develop hypotheses to stratify patients and prioritize indications, guiding clinical oncology development and reverse translation.
• Perform analysis of clinical and biomarker datasets (e.g., large-scale -omics datasets including RNASeq, and Whole Exome/Genome Sequencing) and derive clinically meaningful interpretations.
• Identify potential biomarkers for patient enrichment strategies and gain mechanistic insights of responses and resistances to treatments of interest.
• Drive in-depth analysis of stratified patient data to elucidate biological and driver mechanisms in key oncology indications (integrating multiple omics datasets, including scRNAseq).
• Work with colleagues in the Informatics & Predictive Sciences group to identify drivers of disease heterogeneity and potential therapeutic targets for patients in unmet need.
• Collaborate with experimental teams in the iterative validation of therapeutic and mechanistic therapeutic hypotheses.
• Summarize analysis results and report conclusions to BMS decision-making bodies.

Requirements

• Bachelor's Degree with 7+ years of academic/industry experience, or Master's Degree with 5+ years of academic/industry experience, or PhD with 2+ years of academic/industry experience.
• Strong experience in the use of a high-level programming language such as R, MATLAB, Python or Perl for complex data analysis and reproducible research practices.
• Substantial experience working with Next Generation Sequencing datasets, including RNAseq, scRNAseq, Whole-Genome, Whole-Exome Sequencing and ChipSeq.
• Familiarity with contemporary cloud and high-performance computing environments.
• Expertise in application of contemporary machine-learning/AI approaches.
• Ability to work both independently and collaboratively, and to handle several concurrent, fast-paced projects while conforming with rigorous requirements of clinical studies.
• Strong problem-solving and collaboration skills, rigorous and creative thinking.
• Excellent communication, data presentation, and visualization skills.

Nice-to-haves

• Ph.D. or M.S. with 2+ years of experience in computational biology, bioinformatics, statistics or related fields.
• Experience in biotech or pharmaceutical industries is a plus.
• Fluent written and verbal English language communication.

Benefits

• Medical, pharmacy, dental and vision care.
• Wellbeing support such as the BMS Living Life Better program and employee assistance programs (EAP).
• Financial well-being resources and a 401(K).
• Financial protection benefits such as short- and long-term disability, life insurance, supplemental health insurance, business travel protection and survivor support.
• Work-life programs including paid national holidays and optional holidays, Global Shutdown days between Christmas and New Year's holiday, up to 120 hours of paid vacation, up to two (2) paid days to volunteer, sick time off, and summer hours flexibility.
• Parental, caregiver, bereavement, and military leave.
• Family care services such as adoption and surrogacy reimbursement, fertility/infertility benefits, support for traveling mothers, and child, elder and pet care resources.
• Tuition reimbursement and a recognition program.