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Remote Cancer Bioinformatics Jobs in New York (NOW HIRING)

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Remote Cancer Bioinformatics information

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 key skills and qualifications needed to thrive as a remote cancer bioinformatics specialist?

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 are the most commonly searched types of Cancer Bioinformatics jobs in New York?

The most popular types of Cancer Bioinformatics jobs in New York are:

What are popular job titles related to Remote Cancer Bioinformatics jobs in New York?

For Remote Cancer Bioinformatics jobs in New York, the most frequently searched job titles are:

What job categories do people searching Remote Cancer Bioinformatics jobs in New York look for?

The top searched job categories for Remote Cancer Bioinformatics jobs in New York are:

What cities in New York are hiring for Remote Cancer Bioinformatics jobs?

Cities in New York with the most Remote Cancer Bioinformatics job openings:

Remote Cancer Bioinformatics jobs near you
Infographic showing various Remote Cancer Bioinformatics job openings in New York as of July 2026, with employment types broken down into 3% Locum Tenens, 36% As Needed, 54% Full Time, 4% Part Time, 2% Nights, and 1% Summer. Highlights an 82% Physical, 2% Hybrid, and 16% Remote job distribution.

Scientist- Bioinformatics R&D -REMOTE

SEMA4

Stamford, CT • On-site, Remote

Full-time

This job post has expired today. Applications are no longer accepted.

Job description

Sema4 is a patient-centered health intelligence company dedicated to advancing healthcare through data-driven insights. Sema4 is transforming healthcare by applying AI and machine learning to multidimensional, longitudinal clinical and genomic data to build dynamic models of human health and defining optimal, individualized health trajectories. Centrellis®, our innovative health intelligence platform, is enabling us to generate a more complete understanding of disease and wellness and to provide science-driven solutions to the most pressing medical needs. Sema4 believes that patients should be treated as partners, and that data should be shared for the benefit of all.
We are looking for a talented Scientist- Bioinformatics R&D tojoin our team. The Bioinformatics Scientist leads translational bioinformatics and product development for NGS pipelines as part of the R&D Bioinformatics department. This scientist is an integral part of an interdisciplinary team that develops computational methods and pipelines to interpret large-scale human genome and transcriptome sequencing data from reproductive health, cancer, and other diseases. As part of a development team of engineers and scientists, this scientist will translate research prototypes into production-quality, scalable pipeline products used by a variety of clinical diagnostics and research projects across many teams at Sema4. This scientist will serve as an authority in these products to other users and teams and optimize them to serve Sema4 data science needs.
RESPONSIBILITIES
  • Design, develop, and test NGS pipelines for clinical tests and research projects in oncology, reproductive health, and other indications.
  • Lead or support bioinformatics projects to translate NGS results, as well as public and internal genomic, phenotype, and clinical/EMR datasets, to features and optimizations of clinical utility.
  • Analyze and integrate heterogeneous NGS data (somatic and germline SNVs, indel variants, copy-number alterations, structural variants, gene fusions, transcript isoforms, RNA abundance, RNA editing and modification) from diverse next-generation sequencing assays (Illumina, Ion Torrent, Pacific Biosciences; targeted panels, whole-exome sequencing, whole-genome sequencing, RNA-Seq; bulk and single-cell) and microarrays.
  • Work with wet labs and clinical teams to plan and design experiments to generate such data, and analyze this data.
  • Communicate effectively with collaborators (computational and bioinformatics scientists on R&D and production teams, IT/HPC, clinical lab directors, knowledgebase and curation teams, wet lab staff) to understand and satisfy product and research analysis needs.

QUALIFICATIONS
  • PhD in Bioinformatics, Biomedical Informatics, Computational Biology, Genomics, or a related discipline requiring strong computational and analytical skills supplemented with biology background
  • Hands-on experience working with NGS tools with high proficiency, especially for sequence analysis and expression analysis
  • Strong coding proficiency in R, Python, and SQL programming languages in a Linux environment.
  • Well-versed in the art of effective communication on interdisciplinary teams (scientists, programmers, and clinicians), especially graphical communication about high-complexity datasets to scientific audiences from different backgrounds.
  • High self-motivation, great ability to work in both multiple-task and independent fashions.
  • Good understanding of molecular, cell, and developmental biology, especially where relevant to cancer genomics, oncology, or endocrine neoplasms, and especially molecular cloning and NGS library preparation methodologies.
  • Developing code using distributed version control tools (especially Git) and software issue tracking/management systems (especially Jira).
  • Using or developing genome browsers or other tools for visualization of genomic datasets.

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