Senior Bioinformatician

Goldbelt, Inc.•Atlanta, GA

About The Position

Goldbelt Integrated Logistics Services (GbILS) is seeking a Senior Bioinformatician to serve as the technical lead for sequencing analytics, bioinformatics pipeline development, and computational infrastructure. This individual will provide scientific leadership in the design, implementation, optimization, and maintenance of scalable bioinformatics workflows supporting national wastewater surveillance efforts. The Senior Bioinformatician will collaborate with epidemiologists, laboratory scientists, software engineers, and public health partners to develop innovative analytical solutions that translate complex sequencing data into actionable public health intelligence. This position is contingent upon the successful award of a contract currently under bid.

Requirements

Expert proficiency in Python, R, Bash, and Perl in Linux/HPC environments
Containerization: Docker, Singularity
NGS tools: Bowtie2, SPAdes, Velvet, Prodigal, GATK, QUAST, and related open-source platforms
Phylogenetics: IQ-TREE, BEAST, RAxML, or equivalent
Cloud computing platforms and NoSQL/relational database design
Code versioning: Git, GitHub, GitLab
Minimum 5-8 years of related years of experience
Advanced experience with Nextflow; familiarity with Snakemake and WDL
At least five (5) years of experience in relevant work or related areas

Nice To Haves

Master's or Ph.D. in Bioinformatics, Computational Biology, Computer Science, Genomics, Biology, Microbiology, Public Health, Biostatistics, or closely related scientific discipline
Experience with PySpark preferred
Excellent problem-solving and analytical skills
Strong communication skills, capable of effectively interacting with both technical teams and non-technical stakeholders.
Ability to work independently as well as collaboratively in a team-oriented environment
Previous experience with federal government agencies; preferably with CDC

Responsibilities

Serve as a technical lead and subject matter expert supporting advanced genomic surveillance, outbreak response, and pipeline architecture across multiple program areas.
Lead the design, development, validation, and maintenance of scalable bioinformatics workflows for wastewater sequencing analyses.
Serve as the subject matter expert for computational genomics and metagenomic analyses.
Establish coding standards, workflow documentation, and quality assurance processes for bioinformatics analyses.
Mentor junior bioinformaticians and provide technical oversight on analytical projects.
Review analytical methods, code, and computational workflows to ensure reproducibility and scientific rigor.
Collaborate with epidemiologists, laboratorians, statisticians, and software developers to translate surveillance needs into computational solutions.
Recommend new analytical methods, software tools, and emerging technologies that improve wastewater surveillance capabilities.
Lead development of novel algorithms and computational approaches for variant detection and pathogen characterization.
Support publication of scientific findings through manuscripts, presentations, and technical reports.
Design and maintain scalable cloud-based bioinformatics infrastructure capable of supporting national surveillance data.
Optimize computational performance for high-volume sequencing datasets.
Implement automated quality assurance and quality control monitoring throughout analytical pipelines.
Develop statistical methods to identify variants and potential abundance based on mutations sequencing data sets.
Develop standardized bioinformatics outputs for integration into the platform.
Perform quality control, assembly and analysis of environmental metagenomic sequencing samples.
Manage high-throughput sequencing raw and analytic data files, databases, including uploads to sequencing repositories.
Prepare and deliver clear, concise and accurate reports, presentations, and scientific manuscripts.
Assist with outbreak response.
Lead the design, implementation, and optimization of end-to-end bioinformatics pipelines for wastewater metagenomic sequencing in support of domestic wastewater surveillance for infectious diseases and related environmental monitoring programs.
Develop and curate reference databases for detection and characterization of microbial, viral, fungal, and eukaryotic organisms from environmental and wastewater sample types, including source-specific databases for source attribution analyses.
Develop and validate statistical models to identify variant composition and estimate relative pathogen abundance from wastewater sequencing datasets, integrating mutation profiling and deconvolution approaches.
Lead in silico screening efforts to detect synthetic genomic constructs and engineered sequence features within metagenomic and Whole Genome Sequencing (WGS) datasets, coordinating with biosecurity and laboratory partners to define detection criteria and validate findings.
Design and maintain specialized sequence databases incorporating virulence markers, resistance determinants, strain-type markers, and curated exclusion sequences (e.g., host DNA) to support bio surveillance workflows.
Provide expert bioinformatics support for Whole Genome Sequencing (WGS) of viral pathogens including measles virus and other priority pathogens, encompassing quality control, reference-based assembly, consensus genome generation, variant calling, and phylogenetic analysis.
Support evolutionary modeling of viral genomic data using Bayesian, maximum likelihood, and/or machine learning approaches to inform outbreak investigations and transmission network reconstruction.
Architect, develop, optimize, refactor, and maintain modular, containerized Nextflow pipelines for sequence analysis spanning wastewater metagenomics, isolate Whole Genome Sequencing (WGS), and metagenomic source attribution, ensuring portability across HPC and cloud/hybrid-cloud environments (e.g., AWS, Azure, GCP).
Consult on scaling workflows from desktop to HPC and cloud environments using containerization tools (Docker, Singularity) and workflow management best practices; implement parallelized architectures where appropriate.
Champion code versioning standards and reproducibility practices using Git/GitHub/GitLab; author and maintain comprehensive technical documentation, SOPs, and workflow specifications.
Investigate and implement AI/ML algorithms — including deep learning and Natural Language Processing (NLP)-based approaches — for large-scale genomic pattern recognition, pathogen characterization, and automated feature extraction from scientific literature and surveillance reports.
Advise program staff on novel applications of AI/ML to public health genomic surveillance and recommend approaches appropriate to data scale and biological context.