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Data Scientist II

AXLE INFORMATICS · Remote · posted 4 August 2026

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30
Certified filings · by AXLE INFORMATICS, FY2026 Q2
$129,412
Median filed wage · for “Data Scientist” · 2 filings

Source: US DOL Office of Foreign Labor Certification, LCA disclosure data, FY2026 Q2. Government data is published roughly one quarter in arrears.

This advert was matched to Data Scientist, a job title AXLE INFORMATICS has itself sponsored.

The figure above is not this job’s salary. It is what AXLE INFORMATICS reported to the US Department of Labor for the closest role it has sponsored. A filing history means this employer has sponsored before — it is not a promise that this opening carries sponsorship, and not an offer of pay. Check the advert and ask the employer.

See every role AXLE INFORMATICS has sponsored, and what it paid →

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The role, as AXLE INFORMATICS describes it

(ID: 2026-2574)

Axle is a bioscience and information technology company that offers advancements in translational research, biomedical informatics, and data science applications to research centers and healthcare organizations nationally and abroad. With experts in biomedical science, software engineering, and program management, we focus on developing and applying research tools and techniques to empower decision-making and accelerate research discoveries. We work with some of the top research organizations and facilities in the country including multiple institutes at the National Institutes of Health (NIH).

Benefits We Offer:

  • 100% Medical, Dental & Vision Coverage for Employees
  • Paid Time Off and Paid Holidays
  • 401K match up to 5%
  • Educational Benefits for Career Growth
  • Employee Referral Bonus
  • Flexible Spending Accounts:
  • Healthcare (FSA)
  • Parking Reimbursement Account (PRK)
  • Dependent Care Assistant Program (DCAP)
  • Transportation Reimbursement Account (TRN)

We are seeking a Data Scientist II to join our vibrant team supporting the National Cancer Institute (NCI) at the NIH in Rockville, MD. This role is embedded within NCI's Center for Biomedical Informatics and Information Technology (CBIIT), where you will directly advance cancer research by building the computational infrastructure that scientists depend on every day.

You will support the full omics data lifecycle across a broad spectrum of modalities, including bulk RNA-seq, single-cell RNA-seq (scRNA-seq), spatial transcriptomics, Digital Spatial Profiling (DSP), whole genome and exome sequencing (WGS/WES), metagenomics, metabolomics, and proteomics, as well as clinical, imaging, and biospecimen data. A core part of this role involves developing workflows that integrate these modalities to support systems-level biological questions, cross-cohort studies, and NCI CBIIT initiatives.

You will collaborate closely with NCI scientists, bioinformaticians, clinician-researchers, data engineers, software developers, and government stakeholders to ensure analytical infrastructure is FAIR-compliant, containerized, version-controlled, well-documented, and purpose-built for long-term reuse across the research community.

Key Responsibilities

  • Bioinformatics Workflow and Data Pipeline Development: Design, build, and maintain reproducible pipelines for diverse biomedical data types — including genomic, transcriptomic, single-cell, spatial, proteomic, metagenomic, metabolomic, and clinical datasets. Develop reusable transformation logic and curated datasets supporting analytics, dashboards, APIs, notebooks, and downstream research workflows.
  • Multi-Omics Analysis: Support NCI CBIIT labs in their analysis workflows including bulk RNA-seq (QC, DEG, GSEA), single-cell RNA-seq (clustering, UMAP/t-SNE, cell type annotation, DEG), and Digital Spatial Profiling (annotation, QC, normalization, spatial deconvolution, volcano plots, heatmaps).
  • Data Integration and Lifecycle Support: Enable reliable data movement from source systems into structured, analysis-ready formats. Support ingestion, curation, metadata capture, source-to-target mapping, schema management, provenance tracking, and long-term maintainability of data products.
  • Statistical Modeling and Machine Learning: Apply statistical and ML methods — including hypothesis testing, regression, clustering, PCA, UMAP, t-SNE, and classification — to biomedical datasets. Incorporate AI/LLM-based extraction where appropriate, with clear validation and communication to stakeholders.
  • Researcher-Facing Applications and Visualization: Build and support interactive dashboards (Shiny, Streamlit), notebooks, reports, and APIs enabling researchers to explore multi-omics and clinical data. Support figure generation for QC, differential expression, pathway, and spatial analyses.
  • Collaboration: Partner with data scientists, bioinformaticians, researchers, developers, and government s

Read the full advert and apply on AXLE INFORMATICS’s site →

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