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Python Bioinformatics Jobs in Manhattan, NY (NOW HIRING)

Mount Sinai Health System

Postdoctoral Fellow-MSH

Manhattan, NY · On-site

$53K - $73K/yr

... bioinformatics/data science/machine learning. Requirements: A superior academic performance, proficiency in R, Python,experience with handling ofBigDataand an ability to be self-directed with broadly ...

Ramp

Senior Applied Scientist, Credit Risk

New York, NY · On-site

$165K - $228K/yr

Strong Python experience across exploratory data analysis, predictive modeling, and applied machine ... PhD in Math, Economics, Bioinformatics, Statistics, Engineering, Computer Science, or other ...

Ramp

Senior Applied Scientist, Credit Risk

New York, NY · Remote

$165K - $228K/yr

Strong Python experience across exploratory data analysis, predictive modeling, and applied machine ... PhD in Math, Economics, Bioinformatics, Statistics, Engineering, Computer Science, or other ...

Mount Sinai Hospital

Postdoctoral Fellow-MSH

Manhattan, NY · On-site

$72K - $80K/yr

... bioinformatics/data science/machine learning. Requirements: A superior academic performance, proficiency in R, Python, experience with handling of Big Data and an ability to be self-directed with ...

Formation Bio

Principal Data Scientist

New York, NY · On-site

$204K - $267K/yr

Strong programming skills, particularly in Python * Extensive experience in multi-modal bioinformatics analysis Preferred Qualifications * Proven expertise in cloud computing environments, including ...

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How much do python bioinformatics jobs pay per hour?

As of Jun 10, 2026, the average hourly pay for python bioinformatics in Manhattan, NY is $64.70, according to ZipRecruiter salary data. Most workers in this role earn between $53.32 and $73.51 per hour, depending on experience, location, and employer.

What is a Python Bioinformatics job?

A Python Bioinformatics job involves using Python programming to analyze and interpret biological data, such as DNA sequences, protein structures, and genomic information. Professionals in this role develop algorithms, write scripts, and use bioinformatics libraries like Biopython to process large datasets efficiently. They often work in research institutions, pharmaceutical companies, or healthcare organizations to support scientific discoveries and advancements in medicine. Strong skills in Python, data analysis, and computational biology are essential for success in this field.

Is AI going to replace bioinformatics?

AI is a tool that complements bioinformatics by automating data analysis and pattern recognition, but it is unlikely to fully replace bioinformatics professionals. Bioinformatics roles require domain expertise, interpretation skills, and understanding of biological context that AI cannot fully replicate. Professionals in this field should focus on developing skills in programming, data analysis, and machine learning to stay relevant as AI advances.

What does a typical workday look like for a Python Bioinformatics professional?

A typical workday for a Python Bioinformatics professional often involves developing and maintaining data analysis pipelines, processing large biological datasets, and interpreting results in collaboration with biologists and other researchers. You'll spend substantial time writing scripts, troubleshooting code, and integrating different bioinformatics tools to address specific research questions. Team meetings and presentations are common, as the role requires frequent interaction with cross-functional colleagues. This dynamic environment offers the opportunity to stay engaged with new technologies and make meaningful contributions to scientific discovery.

Is Python enough for bioinformatics?

Python is a widely used programming language in bioinformatics due to its versatility and extensive libraries like Biopython. However, bioinformatics often requires knowledge of other tools, scripting languages, and data analysis techniques to handle complex datasets effectively.

Is Python required for bioinformatics?

Python is widely used in bioinformatics roles because of its simplicity and extensive libraries for data analysis, scripting, and automation. Many bioinformatics jobs require proficiency in Python, along with knowledge of related tools like R or command-line interfaces, to analyze biological data effectively.

What are the key skills and qualifications needed to thrive in the Python Bioinformatics position, and why are they important?

To thrive as a Python Bioinformatics professional, you need a strong foundation in biological sciences, proficiency in Python programming, and experience analyzing complex biological datasets. Familiarity with bioinformatics tools such as Biopython, BEDtools, and databases like NCBI, as well as knowledge of cloud computing platforms and relevant certifications, is commonly expected. Strong problem-solving abilities, attention to detail, and effective communication skills help you collaborate with interdisciplinary teams. These competencies are vital for interpreting biological data accurately, developing reliable pipelines, and advancing research objectives.

What is Python used for in bioinformatics?

In bioinformatics, Python is used for analyzing biological data, such as DNA, RNA, and protein sequences. It supports tasks like data processing, visualization, and automation through libraries like Biopython and Pandas, making it a popular programming language for researchers in the field.
What are popular job titles related to Python Bioinformatics jobs in Manhattan, NY? For Python Bioinformatics jobs in Manhattan, NY, the most frequently searched job titles are:
What job categories do people searching Python Bioinformatics jobs in Manhattan, NY look for? The top searched job categories for Python Bioinformatics jobs in Manhattan, NY are:
Python Bioinformatics jobs near you
Scientist/Senior Scientist, Computational Biology

Scientist/Senior Scientist, Computational Biology

Volastra Therapeutics

New York, NY • On-site

$100K - $136K/yr

Full-time

Posted 15 days ago

Job description

COMPANY
Volastra Therapeutics, Inc. is a clinical-stage oncology biotech company based in New York City, pioneering novel approaches to treating cancer by targeting chromosomal instability (CIN), a unique vulnerability in cancer. Since its founding in 2019, Volastra has grown to support ongoing discovery efforts and a growing clinical organization.
Our lead pipeline programs focus on two distinct inhibitors of KIF18A, a novel therapeutic target. VLS-1488, internally discovered, entered clinical trials in Q4 2023 for the treatment of advanced cancers. Sovilnesib, in-licensed from Amgen in 2023, re-entered the clinic in Q2 2024. Both assets have been granted Fast-Track Designation by the FDA. Volastra is also developing new techniques to understand the biology of chromosomal instability and leveraging these insights to drive forward a preclinical pipeline of therapies against innovative targets.
Volastra is backed by top US and European venture firms such as Arch, Polaris, Vida, Droia, Catalio, and B Capital, alongside strategic investment from Eli Lilly. In addition to venture funding, Volastra has established partnerships with oncology leaders. Our senior leadership team is highly experienced, supported by a world-class advisory board.
We are headquartered in West Harlem, New York City, within easy reach of Columbia, Cornell, Memorial Sloan Kettering, and surrounding areas. Please visit www.volastratx.com for more information.
JOB DESCRIPTION:
We are seeking an outstanding bioinformatics and computational biology scientist to help power Volastra's discovery and translational engine. This person will build and apply rigorous analyses of genomic, transcriptomic, functional genomic, and clinical-translational datasets to identify vulnerabilities, prioritize targets, nominate biomarkers, and connect preclinical findings to patient populations.
This is a hands-on, high-impact role for someone who loves biology, writes excellent code, and can move fluently between exploratory discovery questions and decision-grade analyses. You will partner closely with discovery biologists, translational scientists, chemists, pharmacology colleagues, and the clinical team to generate insight that changes programs.
We want a scientist who is excited to use modern AI coding assistants thoughtfully. AI should accelerate pipeline scaffolding, refactoring, testing, documentation, and exploratory coding, while human judgment, validation, data security, and scientific accountability remain an utmost priority.
Volastra is a fast-paced biotech company of passionate employees, and there is ample opportunity for the ideal candidate to grow and develop with the organization. Individuals will have, from time to time, the opportunity to gain experience with projects outside their direct scope of work.
RESPONSIBILITIES:
  • Lead bioinformatics analyses across discovery sciences and translational sciences, including RNA-seq, single-cell RNA-seq, whole-exome sequencing, whole-genome sequencing, copy number, mutation, structural variant, CRISPR screen, proteomic, or other omics datasets as appropriate.
  • Develop reproducible, well-documented computational workflows for quality control, processing, feature engineering, integrated analysis, visualization, and reporting.
  • Integrate internal experimental datasets with public cancer resources such as TCGA, DepMap, CCLE, CPTAC, cBioPortal, and relevant disease-specific cohorts to prioritize targets and biomarkers.
  • Build analyses that connect cancer genotype, lineage, CIN biology, dependency, perturbation response, and therapeutic hypotheses.
  • Partner with discovery teams to design experiments, interpret results, refine hypotheses, and identify the next best biological test.
  • Support translational strategy by connecting preclinical models, patient genomics, and biomarker hypotheses. Work with clinical colleagues when analyses intersect with clinical samples, patient selection concepts, or exploratory biomarker readouts.
  • Translate complex data into clear recommendations for project teams and leadership, with concise visualizations and transparent assumptions.
  • Build durable code: modular Python and/or R packages, workflow management, data provenance, testing, version control, documentation, containers, and cloud or HPC execution.
  • Use AI coding assistants and LLM-based tools to accelerate code generation, refactoring, unit-test drafting, documentation, pipeline scaffolding, and exploratory analysis. Treat AI output as draft code that must be reviewed, tested, documented, and validated.
  • Help define technical standards for reproducible bioinformatics across the organization and mentor colleagues as appropriate.

REQUIREMENTS:
  • PhD or equivalent experience in bioinformatics, computational biology, genomics, computational oncology, systems biology, bioengineering, computer science, or a related quantitative life-science field.
  • Deep hands-on experience analyzing high-throughput sequencing data, especially transcriptomic and cancer genomic data.
  • Strong coding ability in Python and/or R, with Unix/Linux and bash proficiency.
  • Familiarity with cloud or HPC environments and scalable handling of large biological datasets.
  • Biological insight in oncology, cancer genomics, chromosomal instability, DNA damage response, synthetic lethality, targeted therapy, or drug resistance.
  • Ability to communicate complex analyses to biologists, chemists, translational scientists, clinicians, and leadership with clarity and judgment.
  • High scientific integrity, intellectual ownership, and comfort working in a fast-moving, hypothesis-driven team.
  • Experience in target discovery, biomarker discovery, patient population mapping, translational genomics, or computational oncology.
  • Experience analyzing functional genomics screens, Perturb-seq, CRISPR dependencies, cell line or organoid datasets, pharmacogenomic response data, or multi-omics perturbation studies.
  • Experience building reusable internal tools, structured analysis reports, or lightweight dashboards for project teams.
  • Familiarity with clinical genomics assay outputs and exploratory biomarker workflows.
  • Track record of collaborating with wet-lab scientists to turn computational hypotheses into experiments and decisions.
  • Experience using AI coding assistants, code agents, or LLM-based developer tools in a way that improves quality, speed, testing, and documentation.

Salary Range:
Approximately $140,000 - $180,000 which may vary depending on qualifications, experience, and ultimate leveling. Leveling outside of that stated may be considered for exceptional candidates on a case-by-case basis.

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