Temporary Data Annotation Jobs (NOW HIRING)

About Artiva:

We are a clinical-stage biotechnology company focused on developing natural killer (NK) cell-based therapies. Our mission is to develop effective, safe, and accessible cell therapies for patients with devastating autoimmune diseases. We aim to develop therapies that patients and physicians can utilize in a community setting. Our lead product candidate, AlloNK, is a non-genetically modified, cryopreserved NK cell therapy being evaluated in combination with B-cell targeted monoclonal antibodies (mAbs). We believe the compelling cell killing properties of NK cells, when combined with mAbs for targeting, creates an opportunity to generate potentially transformative therapies.

For more information, visit www.artivabio.com.

Position Summary:

Artiva Biotherapeutics is seeking a part-time/temporary Bioinformatics Data Scientist to help garner biological insights from multimodal biological data. You will design and maintain bioinformatics pipelines, generate insights, and build automated dashboards and reports in collaboration with wet-lab scientists, clinician-researchers, and data engineers.

Responsibilities:

• Design, develop, and maintain bioinformatics pipelines and workflows for diverse biomedical data types including bulk RNA-seq, scRNA-seq, proteomic, and flow cytometric data.
• Perform multi-omics and biomarker analysis including quality control, normalization, batch correction, differential expression analysis, clustering, dimensionality reduction (PCA, UMAP, t-SNE), cell type annotation, comparative analysis, and pathway analysis.
• Support data integration, curation, and lifecycle management including annotation, data ingestion, metadata capture, schema management, and provenance tracking. Enable reliable data movement from source systems into structured, analysis-ready formats.
• Build and support interactive dashboards, visualization tools, notebooks, and reports enabling researchers and clinicians to explore multi-omics, clinical, and sequencing data. Support figure generation for quality control, differential expression, and pathway analyses. Translate complex computational findings into clear biological narratives.
• Collaborate with multidisciplinary teams including wet-lab scientists, bioinformaticians, clinician-researchers, biostatisticians, data engineers, and IT personnel.

Required Qualifications:

• Bachelor’s or master’s degree (preferred) in Computer Science, Data Science, Bioinformatics, Computational Biology, or related field, and demonstrated experience (typically 2+ years) in bioinformatics pipeline development and biological data science.
• Proficiency in Python for analysis, scripting, data science, and visualization. Familiarity with biological computing and data science libraries (e.g., Scanpy, Pandas, NumPy, scikit-learn).
• In-depth knowledge of modern tools and pipelines for processing, aligning, and analyzing multimodal NGS and omics data. Knowledge of standard bioinformatics data formats (FASTQ, FCS) and related processing tools.
• Proficiency with at least one pipeline framework (e.g., Airflow, Snakemake, Nextflow).
• Experience with a cloud computing environment (GCP, AWS, Azure). Proficiency with queryable databases (e.g., PostgreSQL, BigQuery). Ability to work with structured, semi-structured, and unstructured data across relational and data lake environments.
• Awareness of data governance, privacy, and compliance requirements for clinical and research data.
• Strong background in constructing statistical models, hypothesis testing, regression analysis, clustering, and dimensionality reduction techniques. Demonstrated experience with machine learning (ML) methods and applying ML techniques to biological and clinical datasets. Knowledge of differential expression analysis, pathway analysis, and statistical methods relevant to genomic data.

Preferred Qualifications:

• Advanced Development Tools: Experience with frameworks for web application development (Django, Flask, RShiny, Streamlit, React). Experience with CI/CD pipelines.
• Advanced Biomedical Domain Knowledge: Background in biomedical research, clinical research, immunology, or healthcare analytics.
• Governance & Data Management: Experience with metadata management, data lineage, open-source code release, containerized analyses, and secure handling of de-identified or access-controlled research datasets.

Compensation:

Compensation: $55 - 65/hr. Exact compensation may vary based on skills and experience.

If all this speaks to you, come join us on our journey!