Responsibilities
- Analyze diverse and large-scale genomic datasets (e.g., RNA-seq, scRNA-seq, WES/WGS, epigenetic, or multi-omics data) to identify biomarkers, therapeutic targets, or disease mechanisms.
- Apply advanced statistical, machine learning, and data-mining techniques to extract meaningful patterns from noisy biological data.
- Perform quality control, normalization, and batch-correction across heterogeneous datasets.
- Design, optimize, and maintain robust, scalable bioinformatics pipelines.
- Implement version-controlled code architectures to ensure reproducibility and scalability of data analyses.
- Procure and integrate existing biological databases with internal datasets.
- Translate complex computational and statistical findings into clear biological narratives for experimental biologists, clinicians, and stakeholders.
- Collaborate with IT and other functional groups.
Requirements
- Ph.D. or M.S. in Bioinformatics, Computational Biology, Data Science, Genomics, Biology, or a highly quantitative field.
- Proven experience handling genomic data (Next-Generation Sequencing/NGS data analysis is required).
- Ability to turn raw biological data into structured insights.
- Strong experience with AI application in data science.
- Advanced proficiency in R (e.g., Bioconductor, Tidyverse) and/or Python (e.g., Pandas, NumPy, Scikit-learn).
- Experience with standard bioinformatics tools (e.g., alignment tools, variant callers, single-cell toolkits like Seurat/Scanpy).
- A self-starting attitude with an intrinsic desire to stay ahead of the curve in emerging computational methods and biological technologies.
- Proven ability to thrive in a fast-paced environment, manage multiple projects simultaneously, and pivot quickly based on data-driven feedback.
- Exceptional critical thinking skills with a knack for debugging complex code and parsing unstructured data formats.
- Creative, innovative and excellent communication and presentation skills.
Nice to Have
- Experience with cloud computing platforms (AWS, GCP) and containerization (Docker, Singularity) is a strong plus.
Work Arrangement
On-site — Somerset, NJ
