Computational Biologist and AI Engineer (Vaccines)

SGS Consulting; New York (NY); Hybrid; USD 120,000 - 190,000; Full time

Job summary

SGS Consulting is seeking a computational biology specialist to integrate multi-omics data and identify biomarkers for vaccine response and safety. You will design AI-agent solutions to explore and generate insights from diverse datasets and literature, building pipelines and interfaces to support researchers and internal resources.

Collaborate with computational biologists, data scientists, and software engineers to translate needs into scalable AI solutions, writing clean Python code and

Qualifications

• Master's or PhD in computational biology, bioinformatics, computer science or related field.
• Experience analyzing multi-omics datasets for biomedical or vaccine research.
• Strong bioinformatics and software development skills in Python.

Responsibilities

• Integrate and analyze multi-omics datasets to identify biomarkers and molecular signatures for vaccine response and safety.
• Use state‑of‑the‑art methods for bulk RNA‑seq, single‑cell RNA‑seq, TCR/BCR profiling, and immune profiling.
• Design AI-agent solutions to explore, query, integrate, analyze, and generate insights from datasets and literature.
• Build data pipelines and knowledge systems enabling AI agents to retrieve and reason across biological data and research workflows.
• Develop interfaces and APIs to support interaction with internal databases, cloud storage, and bioinformatics pipelines.
• Collaborate with computational biologists, data scientists, and software engineers to translate needs into scalable AI solutions.

Skills

Multi-omics data analysis

Single-cell RNA-seq

Python

AI / LLM development

Biomarker discovery

Documentation

Team collaboration

Education

Master's or PhD in computational biology, bioinformatics, CS or related field

Tools

Python libraries (pandas, scikit-learn)

LLMs

Retrieval-augmented generation

Bioinformatics tools

Job description

Job Responsibilities:

• Integrate and analyze multi-omics datasets, including transcriptomics, proteomics, metabolomics, single-cell profiling, and immune repertoire data, to identify biomarkers and molecular signatures relevant to vaccine response, efficacy, and safety.
• Demonstrate strong familiarity with state-of-the-art methods and tools for bulk RNA-seq, single-cell RNA-seq, TCR profiling, BCR profiling, and immune profiling data analysis.
• Design AI-agent solutions that help researchers explore, query, integrate, analyze, and generate insights from multi-omics datasets and related scientific knowledge.
• Build data pipelines and knowledge systems that allow AI agents to retrieve, summarize, connect, and reason across biological datasets, metadata, research workflows, and scientific literature.
• Develop interfaces and APIs to support interaction with internal databases, cloud storage, bioinformatics pipelines, and external scientific resources.
• Collaborate with computational biologists, data scientists, and software engineers to translate research needs into scalable AI solutions.

Skills:

• Experience analyzing multi-omics datasets for biomedical or vaccine research, such as genetics, bulk RNA-seq, single-cell RNA-seq, spatial omics, immune repertoire profiling, proteomics, or related data types.
• Experience with biomarker discovery, immune-response analysis, or systems immunology, preferably in the context of vaccine, infectious disease, or immunology research.
• Hands‑on experience generating immunological insights from single‑cell sequencing data is highly desirable.
• Expertise in artificial intelligence, large language models, retrieval-augmented generation, agentic AI workflows, or multi-agent system architecture is highly desirable.
• Experience building LLM‑based applications, multi-agent AI systems, agent orchestration workflows, or autonomous research assistants.
• Strong software engineering skills in Python and modern AI development frameworks are preferred.
• Ability to document code thoroughly to ensure reproducibility and clarity for collaborative projects.
• Strong communication and collaboration skills with the ability to work effectively in a hybrid team environment.

Education/Experience:

• Master’s degree or Ph.D. in computational biology, bioinformatics, computer science, AI/ML, data science, immunology, or a related quantitative scientific field.