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Entry Level Bioinformatics Data Scientist Jobs in California

... Scientist to join our team. With a focus on induced proximity therapeutics, you will collaborate ... Apply advanced bioinformatics and machine learning approaches across multi-modal datasets to ...

Support production & commercial development teams with data analysis and interpretation ... and non-scientific backgrounds. * Contribute and author bioinformatics-focused white papers ...

Senior Scientist, Bio AI

Redwood City, CA · On-site

$205K - $235K/yr

The Position Earli Inc. is currently seeking a top caliber Senior Scientist, Bio AI to join our ... Leverage cutting-edge ML, bioinformatics, and high-throughput assay data to design cancer-specific ...

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Entry Level Bioinformatics Data Scientist information

What does an entry level bioinformatics data scientist do?

An Entry Level Bioinformatics Data Scientist applies computational and statistical techniques to analyze biological data, such as DNA sequences or gene expression profiles. They work with large datasets to identify patterns, generate insights, and contribute to research in fields like genomics, drug discovery, or personalized medicine. Their tasks often include data cleaning, developing algorithms, running analyses, and visualizing results for scientific teams. They typically collaborate with biologists, statisticians, and software engineers to solve complex biological problems.

What are the key skills and qualifications needed to thrive as an entry level bioinformatics data scientist?

To thrive as an Entry Level Bioinformatics Data Scientist, you need a solid background in biology, statistics, and computer science, often supported by a relevant degree in bioinformatics or a related field. Familiarity with programming languages such as Python or R, experience with bioinformatics tools like BLAST or Bioconductor, and knowledge of data analysis platforms are typically required. Strong problem-solving skills, attention to detail, and effective communication are important soft skills for interpreting complex data and collaborating with multidisciplinary teams. These skills and qualifications are essential for accurately analyzing biological data, generating meaningful insights, and contributing to research or clinical projects.

What are some typical challenges faced by entry level bioinformatics data scientists during their first year on the job?

Entry level bioinformatics data scientists often encounter challenges such as adapting to complex biological datasets, learning to use specialized bioinformatics tools, and understanding the nuances of interdisciplinary collaboration with biologists and clinicians. Balancing data analysis with ongoing skill development in programming and statistics is another common hurdle. However, most teams provide mentorship and training to help new hires acclimate and build confidence in tackling real-world research problems.

What is the difference between Entry Level Bioinformatics Data Scientist vs Entry Level Bioinformatics Analyst?

AspectEntry Level Bioinformatics Data ScientistEntry Level Bioinformatics Analyst
Required CredentialsBachelor's in Bioinformatics, Biology, Computer Science; some roles prefer internships or certificationsBachelor's in Bioinformatics, Biology, or related field; similar educational background
Work EnvironmentResearch labs, biotech companies, healthcare institutions, academic settingsResearch labs, healthcare, biotech firms, academic institutions
Employer & Industry UsageUsed in biotech, pharma, healthcare, research institutionsCommon in research, healthcare, biotech sectors

Both roles require similar educational backgrounds and work environments, focusing on analyzing biological data. The main difference is that a Bioinformatics Data Scientist often involves more advanced data modeling, machine learning, and statistical analysis, whereas a Bioinformatics Analyst typically concentrates on data processing, visualization, and reporting. Entry Level Bioinformatics Data Scientists tend to handle more complex computational tasks, but both roles serve essential functions in biological research and industry applications.

What are the most commonly searched types of Bioinformatics Data Scientist jobs in California?

The most popular types of Bioinformatics Data Scientist jobs in California are:

What are popular job titles related to Entry Level Bioinformatics Data Scientist jobs in California?

For Entry Level Bioinformatics Data Scientist jobs in California, the most frequently searched job titles are:

What job categories do people searching Entry Level Bioinformatics Data Scientist jobs in California look for?

The top searched job categories for Entry Level Bioinformatics Data Scientist jobs in California are:

What cities in California are hiring for Entry Level Bioinformatics Data Scientist jobs?

Cities in California with the most Entry Level Bioinformatics Data Scientist job openings:

Infographic showing various Entry Level Bioinformatics Data Scientist job openings in California as of August 2026, with employment types broken down into 1% As Needed, 84% Full Time, 13% Part Time, and 2% Contract. Highlights an 86% Physical, 3% Hybrid, and 11% Remote job distribution.

Bioinformatics Data Scientist (Part-time/Temporary)

Artiva Biotherapeutics, Inc.

San Diego, CA

$55 - $65/hr

Temporary

Posted 17 days ago


Job description

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


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