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Remote Bioinformatics Python Jobs in New York, NY

Programming Proven expertise (1-2 years) in - 1. PHP7 and/or Python based development. 2. R ... Master's degree in Bioinformatics or related fields. LOCATION: Hybrid - remote + on-site Additional ...

... bioinformatics * Comfortable coding in Python or R for research or data analysis * Exceptionally ... Fully remote and flexible - work when and where it suits you * Freelance autonomy with the ...

... remote Who You Are Holder of a Master's or PhD in Biology or a closely related field (Genetics, Molecular Biology, Bioinformatics, Biotechnology, etc.) Proficient in Python or R for research or data ...

Remote Bioinformatics Python information

See New York, NY salary details

$14

$64

$94

How much do remote bioinformatics python jobs pay per hour?

As of May 28, 2026, the average hourly pay for remote bioinformatics python in New York, NY is $64.13, according to ZipRecruiter salary data. Most workers in this role earn between $52.88 and $72.84 per hour, depending on experience, location, and employer.

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

To thrive as a Remote Bioinformatics Python professional, you need a strong background in biology, statistics, and computational analysis, typically supported by a degree in bioinformatics, computational biology, or a related field. Expertise in Python programming, familiarity with bioinformatics tools (such as Biopython, pandas, and NumPy), and experience using platforms like Git and Linux are essential. Strong problem-solving, communication, and self-motivation skills help you collaborate effectively and manage projects independently in a remote environment. These skills ensure that you can analyze complex biological data accurately, share insights with interdisciplinary teams, and contribute effectively to research or clinical projects from a remote setting.

How do remote Bioinformatics Python professionals typically collaborate with research teams and handle data security?

Remote Bioinformatics Python professionals often work closely with interdisciplinary research teams, including biologists, statisticians, and software engineers. Collaboration is facilitated through regular video meetings, shared code repositories (like GitHub), and project management tools such as Jira or Trello. Data security is paramount in this field, so professionals must follow strict protocols for accessing and transferring sensitive biological data, often using encrypted channels and adhering to institutional or governmental compliance standards.

What is a Remote Bioinformatics Python job?

A Remote Bioinformatics Python job involves using the Python programming language to analyze biological data, such as DNA, RNA, or protein sequences, from a remote location. Professionals in this role develop algorithms, scripts, and tools to process and interpret complex datasets, often supporting research in genomics, drug discovery, and healthcare. Working remotely allows bioinformaticians to collaborate with global teams and contribute to scientific projects without needing to relocate. These roles typically require strong programming skills, knowledge of bioinformatics concepts, and experience with biological databases.

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

AspectRemote Bioinformatics PythonRemote Genomic Data Analyst
Required SkillsPython, bioinformatics tools, data analysisGenomic data interpretation, statistical analysis, Python (optional)
Work EnvironmentResearch labs, biotech companies, academiaHealthcare institutions, research organizations, biotech firms
Common CertificationsBioinformatics certifications, Python programmingBioinformatics or genomics certifications, data analysis skills

Remote Bioinformatics Python roles focus on developing and applying Python-based tools for biological data analysis, often requiring programming expertise. Remote Genomic Data Analysts interpret genomic datasets, utilizing statistical and bioinformatics skills. Both roles are prevalent in biotech and research industries, but Bioinformatics Python positions emphasize coding, while Genomic Data Analysts focus more on data interpretation and reporting.

What cities near New York, NY are hiring for Remote Bioinformatics Python jobs? Cities near New York, NY with the most Remote Bioinformatics Python job openings:
Scientist- Bioinformatics R&D -REMOTE

Scientist- Bioinformatics R&D -REMOTE

SEMA4

Stamford, CT • On-site, Remote

Full-time

Posted 18 days ago


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.