Bioinformatics Scientist - II (Associate)

Company : Experis

Location : Cambridge, MA, 02140

Posted Date : 2 October 2025

Job Type : Contractor

Category : Scientific Research & Development

Occupation : Scientist

Job Details

Job Title: Bioinformatics Scientist II
Duration: 23 Month Contract
Location: Onsite - 320 Bent St 4th Floor, Cambridge, MA 02141
Pay Range: $70/hr- $77.53/hr
Key Skills:

Required expertise with multi-omics data analysis and integration (e.g., RNA-Seq, single-cell RNA-Seq.
Transcriptomics analysis.
Proficiency in R and Bash.
High-performance computing (HPC) systems and AWS Cloud Computing (e.g., IAM, S3 buckets).

Qualifications:
Required Qualifications:

Ph.D. in Computational Biology or a related field.
A proven track record of over 3 years in multi-omics analysis.
Fundamental understanding of statistical methods and multi-omics data analysis and integration (e.g., RNA-Seq, single-cell RNA-Seq, genotype, spatial transcriptomics, OLINK).
Proficiency in R, Python, and Bash, with the ability to establish best practices for reproducible data analyses.
Experience with high-performance computing (HPC) systems and AWS Cloud Computing (e.g., IAM, S3 buckets).
A collaborative and self-motivated individual with a strong work ethic, capable of managing multiple objectives in a dynamic environment and adapting to changing priorities.
Excellent written and verbal communication skills.

Preferred Qualifications:

Experience in processing and analyzing real-world data.
Familiarity with spatial transcriptomics analysis.
Knowledge of statistical and population genetics principles.

Responsibilities:

Our client's Precision Genetics group within the Data and Genome Sciences Department is seeking a skilled Contractor to join their Computational Precision Immunology team.
They are looking for a data scientist with extensive experience in multi-modal and multi-scale data analyses to contribute to their innovative research efforts.

Key Responsibilities:

Data Ingestion: Query external databases to acquire relevant multi-omics datasets (e.g., PubMed, Gene Expression Omnibus, ArrayExpress, gnomAD, GTEx, Ensembl).
RNA-seq Analysis: Perform quality control (QC) and analysis of bulk and single-cell RNA-seq data using state-of-the-art methods (e.g., FastQC, STAR, Limma, DESeq2, clusterProfiler, Seurat, scanpy, LeafCutter).
Multi-Omics Analysis: Analyze diverse molecular data types including spatial transcriptomics (e.g., Slide-seq, MERFISH, squidpy) and proteomics (e.g., OLINK, mass spectrometry-based approaches).
Data Integration: Integrate multi-omics datasets, including gene/protein expression, mRNA splicing, spatial transcriptomics, and genotype data.
Documentation: Prepare detailed documentation of analysis methods and results in a timely manner.