Data Scientist - Oncology & Computational Biology

Job Description:

Job Title: Scientist (Data Scientist - Oncology & Computational Biology)

Location: Ridgefield, CT (Remote)

Duration: 12 Months

Work Schedule: 40 hours per week (8 hours per day)

Position Overview

Boehringer Ingelheim is seeking a highly motivated Scientist III to join the Computational Innovation Department and support oncology drug discovery research through advanced computational and data-driven approaches. This role will focus on leveraging multi-modal omics data, bioinformatics methodologies, and statistical analysis to generate biological insights that accelerate the discovery and development of novel cancer therapeutics.

The successful candidate will work closely with cross-functional scientific teams, including biologists and drug discovery researchers, to address complex scientific challenges and contribute to oncology research programs.

Key Responsibilities

Oncology Research & Drug Discovery

• Support oncology drug discovery and development initiatives through computational and bioinformatics approaches.
• Collaborate with biologists, researchers, and cross-functional teams to solve complex scientific problems.
• Generate actionable biological insights that advance therapeutic discovery programs.

Data Science & Bioinformatics

• Analyze and integrate multi-modal omics datasets using advanced statistical and computational techniques.
• Identify, acquire, process, and analyze both publicly available and internally generated biological datasets.
• Develop and implement innovative analytical methods when conventional approaches are insufficient.
• Apply emerging data science technologies and methodologies to support therapeutic research and development.

Scientific Analysis & Communication

• Stay current with scientific literature and emerging trends in computational biology, bioinformatics, and oncology research.
• Interpret, summarize, and present analytical findings to scientific stakeholders and collaborators.
• Communicate complex data-driven insights clearly and effectively to both technical and non-technical audiences.

Data Integrity & Reproducibility

• Ensure data analyses adhere to FAIR principles (Findable, Accessible, Interoperable, and Reusable).
• Maintain comprehensive documentation, reproducible workflows, and high standards of scientific integrity and ethics.

Required Qualifications

Education

• Ph.D. from an accredited institution in a relevant scientific discipline, including but not limited to:
• Computational Biology
• Bioinformatics
• Genomics
• Biostatistics
• Computer Science
• Computational Science
• Biological Sciences
• Related quantitative or life science fields

Technical Skills

• Strong programming experience in:
• Python
• R
• Experience performing bioinformatics analyses within Unix/Linux environments.
• Hands-on experience with:
• Bulk Next-Generation Sequencing (NGS) data
• Single-cell sequencing data analysis
• Proficiency working with High-Performance Computing (HPC) environments and clusters.
• Experience conducting biological pathway analysis and interpretation.

Preferred Qualifications

• Experience in one or more of the following areas is highly desirable:
• Oncology or immunology research
• Spatial transcriptomics
• DNA methylation analysis
• Liquid biopsy data analysis
• Multi-omics data integration
• Public oncology and genomics databases, including:
• TCGA (The Cancer Genome Atlas)
• GTEx
• Human Cell Atlas
• CZ CELLxGene Discover
• Human Tumor Atlas Network (HTAN)
• Similar large-scale biomedical datasets