Company Description
At Bridge Informatics, we specialize in developing custom data-driven solutions for life science customers. Our mission is to bridge the gap between bench researchers and bioinformaticians, practice and theory, and data and insight to provide efficient, interdisciplinary solutions for our clients. Join our team and work on innovative projects that advance precision medicine.
The Role
This Bioinformatics Scientist role is truly end-to-end. You'll be involved from the very beginning, collaborating with clients to understand their needs and define the project's scope. You'll then translate these discussions into a clear and comprehensive statement of work (SOW), outlining the project's objectives, deliverables, and timelines. Once the project is underway, you'll be responsible for executing the data analysis, utilizing your expertise to uncover insights and trends, within the time estimates you quoted during the SOW phase. Finally, you'll communicate your findings effectively through compelling presentations and reports, ensuring that the project's impact is understood by all stakeholders. You’ll be supported by BI’s Head of Business Development and one of BI’s Project Managers.
Responsibilities
- Work closely with the Head of Business Development and/or directly with clients to understand their research goals
- Work with the Head of Business Development to draft a Statement of Work (SOW) that details your recommended analysis and the completion criteria as discussed with our client
- Lead and execute end-to-end, single-cell sequencing data analysis, from pre-processing to advanced downstream analysis, for diverse client projects across a wide variety of domains in genomics and bioinformatics, within the time estimates you quoted during the SOW phase
- Data type examples include scRNA-seq, DNAseq, bulk RNAseq, MicroArray, GWAS, WES
- Build and refine custom script-based pipelines for single-cell data analysis, utilizing industry best practices and tools
- Present analysis results via scientific reports and presentations to external stakeholders
- Deliver and install pipeline code for future utility
- You may be asked to assist with the maintenance of and improvements to existing client genomic/transcriptomic pipelines, bioinformatics tools, and related software and systems
- You may be asked to support projects involving bulk sequencing data processing, analysis, and tool building
Required Skills
- PhD or equivalent in Bioinformatics, Computational Biology, or a related discipline with a strong focus on single-cell genomics (learned on the job or self-taught).
- Extensive experience in single-cell data analysis, demonstrated through publications, projects, or industry work
- Ability to clearly articulate complex scientific concepts to diverse audiences - most of which aren’t familiar with scRNA seq - and work effectively in a team environment
- Ability to forecast the number of hours each sub-task in an analysis will likely require
Qualifications
- Demonstrated experience in single-cell RNAseq data preprocessing, processing, analysis, and visualization
- Demonstrated experience in bulk RNAseq data preprocessing, processing, analysis and visualization
- Demonstrated experience and confidence in writing code in Python or R
- Demonstrated experience in using cloud platforms (one of the following: AWS, GCP, Azure)
- Demonstrated experience in using containerization platforms ( ex – Docker)
- Demonstrated experience in workflow/pipeline management systems (ex – SnakeMake, NextFlow)
Please note: The ideal candidate needs to be focused on extracting insight from the work with scientists of different backgrounds and not necessarily a perfectionist in creating production-level tools. For this reason, we look highly upon those with previous work at the bench. Ideally, this candidate has experience optimizing assays and understands the importance of basic lab skills, such as when and why one should use positive and negative controls.
Preferred Experience and Skills:
- Bench top experience (aka wet lab skills) previous to your time as a bioinformatics expert
- Knowledge of immunology or cancer biology a plus.
- Critical thinking around experimental design, statistical hypothesis testing, and biological interpretation.
- Capable of integrating information generated from multiple sources to strengthen research hypotheses.
- Experience with high-performance Linux cluster and cloud computing
- Experience with machine learning or statistical inference techniques is a plus.