What are the responsibilities and job description for the Data Scientist - Oncology & Computational Biology position at Aequor?
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