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Remote Cancer Bioinformatics Jobs in California (NOW HIRING)

Veracyte

Data Scientist II

San Diego, CA · On-site +1

$101K - $140K/yr

... cancer biology * Experience working with real world clinical data. #LI-Hybrid, or #LI-Remote The ... bioinformatic and AI capabilities, and a powerful evidence-generation engine, which ultimately ...

Freenome

Senior Software Engineer II

Brisbane, CA · Remote

$161K - $227K/yr

... of cancer. The role reports to our engineering management team. This role will be a Remote role ... Domain-specific experience in computational biology, genomics, bioinformatics, or a related field.

Freenome

Senior Software Engineer II

Brisbane, CA · Remote

$161K - $227K/yr

... of cancer. The role reports to our engineering management team. This role will be a Remote role ... Domain-specific experience in computational biology, genomics, bioinformatics, or a related field.

Tempus

Data Scientist II, Outcomes Research

Redwood City, CA · On-site +1

$100K - $150K/yr

Advanced degree (Master's with 2+ years experience or equivalent) in data science, bioinformatics ... Experience working in oncology and/or analyzing outcomes related to cancer genetics, immunology, or ...

All JobsRemote Cancer Bioinformatics JobsRemote Cancer Bioinformatics Jobs in California

Remote Cancer Bioinformatics information

What are the key skills and qualifications needed to thrive as a Remote Cancer Bioinformatics Specialist, and why are they important?

To thrive as a Remote Cancer Bioinformatics Specialist, you need a strong background in bioinformatics, molecular biology, and statistical analysis, typically supported by an advanced degree in bioinformatics or a related field. Proficiency with bioinformatics tools (such as R, Python, Bioconductor), databases (like TCGA), and experience with cloud computing or high-performance computing environments is often required. Strong problem-solving abilities, attention to detail, and effective remote communication set top professionals apart in this field. These skills ensure accurate data analysis, clear collaboration with research teams, and meaningful contributions to cancer research and patient outcomes.

What are some common challenges faced by remote cancer bioinformatics professionals and how can they be addressed?

Remote cancer bioinformatics professionals often face challenges such as effective collaboration with multidisciplinary teams, managing large and sensitive datasets securely, and staying updated with rapidly evolving analytical tools. To address these, it's important to leverage secure cloud-based platforms for data sharing, participate in regular virtual meetings, and engage in continuous learning through online courses and webinars. Building strong communication channels and maintaining clear documentation also help ensure smooth teamwork and project progress.

What is the difference between Remote Cancer Bioinformatics vs Remote Genomic Data Analyst?

AspectRemote Cancer BioinformaticsRemote Genomic Data Analyst
Required CredentialsBachelor's/Master's in Bioinformatics, Biology, or related fields; experience with cancer datasetsBachelor's/Master's in Genomics, Data Science, or related fields; experience with genomic data analysis
Work EnvironmentRemote, research labs, biotech companiesRemote, healthcare organizations, research institutions
Industry UsagePrimarily in cancer research, biotech, pharmaHealthcare, research, biotech

Remote Cancer Bioinformatics focuses on analyzing cancer-specific datasets to understand tumor biology, while Remote Genomic Data Analysts handle broader genomic data across various fields. Both roles require similar educational backgrounds and often work remotely for research or biotech companies, but their specific datasets and applications differ.

What is a Remote Cancer Bioinformatics specialist?

A Remote Cancer Bioinformatics specialist is a professional who uses computational tools and data analysis techniques to study cancer-related biological data, such as genetic sequences or patient records, while working remotely. They collaborate with researchers, clinicians, and other scientists to interpret large datasets and uncover insights that can help in cancer diagnosis, treatment, and research. This role typically involves programming, statistical analysis, and the use of specialized bioinformatics software to answer complex biological questions about cancer.
What are the most commonly searched types of Cancer Bioinformatics jobs in California? The most popular types of Cancer Bioinformatics jobs in California are:
What are popular job titles related to Remote Cancer Bioinformatics jobs in California? For Remote Cancer Bioinformatics jobs in California, the most frequently searched job titles are:
What job categories do people searching Remote Cancer Bioinformatics jobs in California look for? The top searched job categories for Remote Cancer Bioinformatics jobs in California are:
What cities in California are hiring for Remote Cancer Bioinformatics jobs? Cities in California with the most Remote Cancer Bioinformatics job openings:
Remote Cancer Bioinformatics jobs near you
Machine Learning Engineer (Remote)

Machine Learning Engineer (Remote)

Astrix Inc

South San Francisco, CA • On-site, Remote

$55 - $73/hr

Full-time

Posted 18 days ago

Job description

Our client is a leader in healthcare innovation, seamlessly integrating pharmaceutical development, diagnostic solutions, and advanced technology and data capabilities.
Title: Machine Learning Engineer (Contract)
Pay rate: $55-73/hr+ (Depends on experience)
Location: Remote in the US or Canada, or onsite in SSF. Must be available during PST hours.
Duration: Through Dec. 2026 (Likely to get extended)
Overview:
Seeking a Machine Learning Bioinformatics Engineer to develop and deploy advanced ML solutions supporting pharmaceutical R&D. This role focuses on analyzing large-scale, multimodal clinicogenomic datasets (genomic, transcriptomic, clinical, and real-world data) to drive insights into disease biology, patient stratification, and treatment response. Ideal candidates are strong in both machine learning and bioinformatics, with a passion for translating complex data into impactful discoveries.
Key Responsibilities:
  • Build and deploy scalable, production-ready machine learning models
  • Process and analyze genomic and transcriptomic data using bioinformatics pipelines
  • Prepare high-quality, normalized biological datasets for downstream analysis
  • Train large-scale models using frameworks like PyTorch Lightning and Hugging Face
  • Develop cloud-based ML solutions (AWS/GCP) with a focus on scalability and reproducibility
  • Collaborate with cross-functional teams to uncover biomarkers and therapeutic targets
  • Provide technical input and guidance on ML system design and implementation

Qualifications:
  • PhD with 0-2 years of relevant work experience, or MS with 3-5 years of relevant work experience, or BS with 4-7 years of relevant work experience.
  • Proficient programming skills: Strong Python programming skills with extensive experience in ML and data libraries (e.g., NumPy, pandas, PyTorch).
  • Deep ML expertise: Excellent knowledge of modern machine learning methods and development best practices, including training strategies, model validation, performance visualization, and experimental design.
  • Deep bioinformatic expertise: Proficient knowledge of bioinformatic processing pipelines for genomic and transcriptomic variables.
  • Strong knowledge of computational oncology, cancer genomics and analysis of clinicogenomics datasets.
  • Must be authorized to work in the United States

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