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Axle

Data Scientist II

RemoteUnited States only
Published
Role
Data Science
$130k–$145k/yr
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Open to US only. Set where you work from to check your eligibility.

No BS summary

Data scientist/bioinformatician for biomedical research, strong in Python and R. Must have hands-on experience with at least two omics data types and statistical/ML analysis. US-only signals from remote role with 401K and US-style benefits.

Core skills

PythonRBioinformatics workflows

Optional skills

SnowflakeDatabricksCloud data warehousesGalaxyTerraNextflowWDLSnakemake

What you'll do

  • 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.
  • 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).
  • 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.
  • 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.
  • 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.
  • Partner with data scientists, bioinformaticians, researchers, developers, and government stakeholders to translate scientific needs into technical specifications, data models, and reusable workflows that accelerate biomedical research.
  • Individuals may be required to perform duties outside of their position, job description or responsibilities as needed.

What they require

  • Bachelor's degree in Data Science, Bioinformatics, Computer Science, Biological Sciences, or a related field (advanced degree preferred), or equivalent experience.
  • Demonstrated experience in a data-intensive role supporting biomedical research or scientific computing.
  • Strong proficiency in Python and R for analysis, scripting, and visualization.
  • Hands-on experience with at least two omics data types (e.g., bulk RNA-seq, scRNA-seq, spatial transcriptomics, proteomics, metagenomics, GWAS).
  • Solid understanding of statistical modeling, dimensionality reduction, clustering, differential expression, and pathway analysis.
  • Ability to work with structured, semi-structured, and unstructured data across relational and data lake environments.
  • Strong problem-solving skills with the ability to communicate effectively across technical and non-technical audiences.
  • Able to translate scientific needs into technical solutions and clearly articulate risks, assumptions, and limitations.
  • Genuine interest in biomedical and translational research.
  • Ability to quickly learn domain-specific terminology and workflows, with awareness of data governance, privacy, and compliance requirements for clinical and research data.
  • Preferred: Bachelor's degree in Data Science, Bioinformatics, Computer Science, Biological Sciences, or a related field: advanced degree preferred.
  • Preferred: Experience building analytics solutions in platforms such as Snowflake, Databricks, or cloud data warehouses, with integrations across databases, APIs, dashboards, and application environments.
  • Preferred: Experience with workflow and reproducibility tools used in Galaxy, Terra, Nextflow/WDL, Snakemake, Singularity, or CWL.
  • Preferred: Familiarity with the scverse Python ecosystem (Scanpy, Squidpy, SCIMAP, AnnData) and spatial single-cell analysis methods, including PhenoGraph, Louvain/Leiden clustering, UMAP, and Ripley's L statistic, is a plus.
  • Preferred: Experience preparing curated datasets for dashboards, APIs, and web applications.
  • Preferred: Familiarity with Posit Connect, R/Shiny, Streamlit, Jupyter, or similar platforms is a plus.
  • Preferred: Experience with AWS (EC2, S3, Lambda), object storage, relational databases, scheduled jobs, API integrations, and secure data movement.
  • Preferred: Familiarity with HPC environments, SLURM/SGE, or NIH Biowulf is preferred.
  • Preferred: Background in biomedical research, clinical research, or healthcare analytics.
  • Preferred: Familiarity with standards such as HL7/FHIR, CDISC, or OMOP, and experience with clinical, genomic, or biospecimen data is a plus.
  • Preferred: Experience with metadata management, data lineage, open-source code release, containerized analyses, and secure handling of de-identified or access-controlled research datasets.
  • Preferred: Experience creating documentation, training materials, or workshops for researchers and non-coder audiences.
  • Preferred: Ability to support tool adoption and explain workflows and results clearly is strongly preferred.

Benefits

  • 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)

Axle powers mission-critical insurance data extraction, validation, and verification for companies including Fortune 500 banks and brands like Hertz, Avis, and Audi.

InsuranceStartupaxle.insure
$130k–$145k/yr