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Bioinformatics Data Analyst Jobs in New York (NOW HIRING)

NYULMC

Sr. Bioinformatics Developer

New York, NY · On-site

Create data marts and analytical datasets from harmonized molecular testing data to enable ... Master's degree in Bioinformatics, Computational Biology, Computer Science, or related field ...

NYULMC

Senior Bioinformatics Programmer

New York, NY · On-site

In addition, bioinformatics analysis of various types of patient genomic, epigenomic and transcriptomic data is required. This is a great opportunity to be involved in an innovative environment ...

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How much do bioinformatics data analyst jobs pay per hour?

As of Aug 24, 2026, the average hourly pay for bioinformatics data analyst in New York is $50.13, according to ZipRecruiter salary data. Most workers in this role earn between $39.47 and $53.65 per hour, depending on experience, location, and employer.

What is a bioinformatics data analyst?

Bioinformatics Data Analysts are professionals who use computational tools and methods to analyze biological data, such as genomic sequences or protein structures. They work at the intersection of biology, computer science, and statistics to interpret complex datasets and draw meaningful insights for research or clinical applications. Their work supports areas like drug discovery, personalized medicine, and evolutionary biology. Typically, they collaborate with biologists, software engineers, and statisticians to solve complex biological problems. Strong analytical skills and proficiency with data analysis software are essential for this role.

How do bioinformatics data analysts collaborate with researchers and other team members?

Bioinformatics Data Analysts often work closely with biologists, clinicians, and software engineers, acting as a bridge between experimental research and computational analysis. Collaboration usually involves interpreting experimental data, discussing analytical approaches, and presenting findings in a way that's accessible to non-technical stakeholders. Regular team meetings and project updates are common, and strong communication skills are essential for translating complex data insights into actionable information for the broader research team. This multidisciplinary teamwork fosters innovation and ensures that analyses align with the goals of larger research projects.

What are the key skills and qualifications needed to thrive as a bioinformatics data analyst?

To thrive as a Bioinformatics Data Analyst, a solid background in biology, statistics, and programming (often with a degree in bioinformatics, computational biology, or a related field) is essential. Proficiency with tools such as R, Python, SQL, and bioinformatics software like BLAST or Bioconductor, as well as experience with large datasets and relevant certifications, is typically required. Strong analytical thinking, attention to detail, and effective communication skills help analysts interpret complex data and collaborate with interdisciplinary teams. These skills ensure accurate data analysis, meaningful biological insights, and successful project outcomes in research or clinical settings.

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

AspectBioinformatics Data AnalystBioinformatics Scientist
Required CredentialsBachelor's or Master's in Bioinformatics, Biology, or related fieldsMaster's or PhD in Bioinformatics, Computational Biology, or related fields
Work EnvironmentData analysis teams, research labs, healthcare settingsResearch projects, development of algorithms, scientific publications
Employer & Industry UsageBiotech companies, healthcare institutions, research organizationsAcademic institutions, biotech firms, pharmaceutical companies
Common Search & ComparisonOften compared for data analysis roles in bioinformaticsMore research-focused, involved in algorithm development

Bioinformatics Data Analysts primarily focus on analyzing biological data using existing tools, while Bioinformatics Scientists develop new algorithms and conduct research. Both roles require strong computational skills, but the Scientist role typically involves more advanced research and innovation.

What are popular job titles related to Bioinformatics Data Analyst jobs in New York?

For Bioinformatics Data Analyst jobs in New York, the most frequently searched job titles are:

What job categories do people searching Bioinformatics Data Analyst jobs in New York look for?

The top searched job categories for Bioinformatics Data Analyst jobs in New York are:

What cities in New York are hiring for Bioinformatics Data Analyst jobs?

Cities in New York with the most Bioinformatics Data Analyst job openings:

Bioinformatics Data Analyst jobs near you
Infographic showing various Bioinformatics Data Analyst job openings in New York as of August 2026, with employment types broken down into 1% As Needed, 83% Full Time, 13% Part Time, and 3% Contract. Highlights an 85% Physical, 4% Hybrid, and 11% Remote job distribution, with an average salary of $104,270 per year, or $50.1 per hour.

Scientist/Sr. Scientist, Bioinformatics Data

Legend Biotech US

Somerset, NJ • Hybrid

Full-time

Re-posted 8 days ago

Job description

Legend Biotech is seeking a Scientist/Sr. Scientist, Bioinformatics Data as part of the Early Drug Development team based in Somerset, NJ.

Role Overview

We are seeking a highly motivated, passionate, and driven Bioinformatics Data Scientist with high scientific curiosity to join our research and development team. In this role, you will bridge the gap between complex biological datasets and actionable therapeutic insights. You will design, develop, and execute scalable computational pipelines to analyze high-dimensional genomic data.The ideal candidate possesses a deep curiosity for biological systems, an analytical mindset, and the technical skillset to tackle unstructured, diverse and complex multiomics challenges. Whether you come from a deep biological background with strong computational skills or a data science background with a proven track record in working with biological data, you will play a critical role in accelerating both our discovery and clinical pipeline.

Key Responsibilities 

  • Analyze diverse and large-scale genomic datasets (e.g., RNA-seq, scRNA-seq, WES/WGS, epigenetic, or multi-omics data) to identify biomarkers, therapeutic targets, or disease mechanisms.
  • Apply advanced statistical, machine learning, and data-mining techniques to extract meaningful patterns from noisy biological data.
  • Perform quality control, normalization, and batch-correction across heterogeneous datasets.
  • Design, optimize, and maintain robust, scalable bioinformatics pipelines.
  • Implement version-controlled code architectures to ensure reproducibility and scalability of data analyses.
  • Procure and integrate existing biological databases with internal datasets.
  • Translate complex computational and statistical findings into clear biological narratives for experimental biologists, clinicians, and stakeholders.
  • Collaborate with IT and other functional groups.

Requirements

  • Ph.D. or M.S. in Bioinformatics, Computational Biology, Data Science, Genomics, Biology, or a highly quantitative field.
  • Proven experience handling genomic data (Next-Generation Sequencing/NGS data analysis is required).
  • Ability to turn raw biological data into structured insights.
  • Strong experience with AI application in data science.
  • Advanced proficiency in R (e.g., Bioconductor, Tidyverse) and/or Python (e.g., Pandas, NumPy, Scikit-learn).
  • Experience with standard bioinformatics tools (e.g., alignment tools, variant callers, single-cell toolkits like Seurat/Scanpy).
  • Experience with cloud computing platforms (AWS, GCP) and containerization (Docker, Singularity) is a strong plus.
  • A self-starting attitude with an intrinsic desire to stay ahead of the curve in emerging computational methods and biological technologies.
  • Proven ability to thrive in a fast-paced environment, manage multiple projects simultaneously, and pivot quickly based on data-driven feedback.
  • Exceptional critical thinking skills with a knack for debugging complex code and parsing unstructured data formats.
  • Creative, innovative and excellent communication and presentation skills.
  • This role is designed as the starting point of group effort to solve complex biological and clinical problems in a fast paced environment. We look for individuals who take extreme ownership of their expertise and training, and driven by the prospect of turning data into information, and information into knowledge.

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