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Computational Science Jobs in New York (NOW HIRING)

Neptune Bio

Computational Biologist

New York, NY · On-site

The ideal candidate is an independent thinker with strong computational and quantitative skills, and the ability to collaborate closely with both experimental and computational scientists. You will ...

Neptune Bio

Computational Biologist

New York, NY · On-site

The ideal candidate is an independent thinker with strong computational and quantitative skills, and the ability to collaborate closely with both experimental and computational scientists. You will ...

micro1 AI

Computational Biologist - AI Reviewer

Newark, NJ · On-site +1

$90 - $120/hr

Remote micro1 is engaging Computational Biology Experts to contribute their advanced scientific knowledge to a dynamic customer project. In this role, you'll apply your expertise to help train next ...

micro1 AI

Computational Biologist - AI Reviewer

Yonkers, NY · On-site +1

$90 - $120/hr

Remote micro1 is engaging Computational Biology Experts to contribute their advanced scientific knowledge to a dynamic customer project. In this role, you'll apply your expertise to help train next ...

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Computational Science information

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$61.8K

$90.9K

$107.2K

How much do computational science jobs pay per year?

As of Aug 4, 2026, the average yearly pay for computational science in New York is $90,924.00, according to ZipRecruiter salary data. Most workers in this role earn between $84,800.00 and $102,300.00 per year, depending on experience, location, and employer.

What are some common challenges faced by computational scientists when working on interdisciplinary projects?

Computational scientists often collaborate with experts from fields like biology, physics, or engineering, which can present challenges in bridging gaps in domain-specific knowledge and communication styles. Adapting computational models to fit the unique requirements of different disciplines, while ensuring accuracy and efficiency, is a frequent hurdle. Additionally, managing large datasets and integrating diverse computational tools requires strong technical and organizational skills. Open communication and a willingness to learn from colleagues are key to overcoming these challenges and achieving successful project outcomes.

What are the key skills and qualifications needed to thrive as a computational scientist, and why are they important?

To thrive as a Computational Scientist, you need a strong background in mathematics, programming (such as Python, C++, or MATLAB), and domain-specific scientific knowledge, often supported by an advanced degree in a relevant field. Familiarity with high-performance computing (HPC) systems, parallel processing frameworks, and scientific data analysis tools is typically required. Excellent problem-solving skills, collaboration, and effective communication set top candidates apart in interdisciplinary research environments. These skills and qualities are crucial for driving innovative scientific discovery and translating complex data into actionable insights.

What is the difference between Computational Science vs Data Scientist?

AspectComputational ScienceData Scientist
Required CredentialsDegree in science, engineering, or computational fields; often requires advanced degreesDegree in statistics, computer science, or related fields; often requires knowledge of programming and analytics
Work EnvironmentResearch labs, universities, industry R&D departmentsTech companies, finance, healthcare, consulting firms
Industry UsageScientific research, simulation, modelingData analysis, predictive modeling, business insights
Common Search/ComparisonYesYes

Computational Science focuses on developing models and simulations to solve scientific and engineering problems, often requiring advanced degrees and research environments. Data Scientists analyze large datasets to extract insights and support decision-making, typically working in business or tech sectors. While both roles involve programming and data handling, their primary goals and work settings differ significantly.

What can you do with a computational science degree?

A computational science degree prepares individuals for roles such as computational scientist, data analyst, simulation engineer, or research scientist. Graduates often work in industries like technology, healthcare, finance, or government, utilizing skills in programming, modeling, and data analysis to solve complex problems. Proficiency in tools like Python, MATLAB, or high-performance computing environments is common in these roles.

Is computational science a good career?

Computational science is a viable career that involves using computer models, simulations, and data analysis to solve complex scientific problems. It typically requires strong skills in programming, mathematics, and domain knowledge, and offers opportunities in research, industry, and academia with competitive salaries and growth potential.

What is computational science?

Computational science is an interdisciplinary field that uses advanced computing capabilities to understand and solve complex problems. It combines elements of mathematics, computer science, and domain-specific knowledge to create simulations, analyze data, and model physical, biological, or social systems. Computational scientists develop algorithms and use high-performance computing to tackle problems that are difficult or impossible to solve analytically. This field is essential in areas such as climate modeling, drug discovery, engineering, and physics.
What are popular job titles related to Computational Science jobs in New York? For Computational Science jobs in New York, the most frequently searched job titles are:
What job categories do people searching Computational Science jobs in New York look for? The top searched job categories for Computational Science jobs in New York are:
What cities in New York are hiring for Computational Science jobs? Cities in New York with the most Computational Science job openings:
Computational Science jobs near you
Infographic showing various Computational Science job openings in New York as of July 2026, with employment types broken down into 70% Full Time, 29% Part Time, and 1% Contract. Highlights an 71% Physical, 2% Hybrid, and 27% Remote job distribution, with an average salary of $90,924 per year, or $43.7 per hour.

Computational Biologist

Neptune Bio

New York, NY • On-site

Other

Re-posted 2 days ago

Job description

Position Summary

We are seeking a Computational Biologist who is passionate about using data-driven, scalable methods to reveal biological insights. The ideal candidate is an independent thinker with strong computational and quantitative skills, and the ability to collaborate closely with both experimental and computational scientists. You will design, implement, and scale computational pipelines for single-cell perturbation datasets, while contributing to model development and experimental design.

This is a unique opportunity to join a dynamic, interdisciplinary environment and help shape Neptune Bio's computational strategy and infrastructure.

Key Responsibilities

  • Develop, innovate, and maintain advanced computational methods to process, analyze, and interpret large-scale single-cell genomics and perturbation datasets.
  • Collaborate with wet-lab and computational teams to integrate data from diverse experimental modalities and guide experimental design.
  • Build, optimize, and scale data analysis pipelines using modern cloud computing environments (e.g., AWS, GCP, Azure).
  • Contribute to Neptune Bio's data infrastructure, ensuring reproducibility, scalability, and efficient access to large datasets.
  • Stay current with advances in computational biology, machine learning, and scalable infrastructure, applying them to ongoing research challenges.
  • Communicate findings clearly through reports, visualizations, and presentations to multidisciplinary audiences.

Qualification and Education Requirements

You must have:

  • Ph.D. in Bioinformatics, Computational Biology, Computer Science, or a related quantitative field, OR equivalent experience (e.g., BS/MS with 3 years of relevant experience).
  • Proficiency in Python, R, and Unix/Linux environments
  • Demonstrated experience in single-cell or multi-omics data analysis.
  • Solid understanding of statistics, data modeling, and modern machine learning approaches.
  • Experience deploying and scaling computational pipelines on cloud platforms (AWS, GCP, or similar).
  • Strong communication skills and enthusiasm for working in a collaborative, fast-paced environment.

Additional preferred experience includes:

  • Background in functional genomics, CRISPR screens, or perturb-seq analysis.
  • Experience integrating multi-source data to derive novel and impactful insights.
  • Expertise in data engineering and reproducible research tools (e.g., Docker, Nextflow, Snakemake) as well as familiarity with cloud-native architectures and distributed compute.
  • Strong publication record demonstrating innovation in computational methods or biological data analysis.
  • Experience with deep learning frameworks such as PyTorch or TensorFlow.

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