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Scientific Computing Jobs in New York (NOW HIRING)

Pfizer

Staff Engineer, Sr. Manager

New York, NY · Hybrid

$124K - $207K/yr

You will collaborate with HPC engineers and scientific computing specialists to develop scalable cloud native infrastructure that underpins modernization of the scientific computing platform. ROLE ...

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Scientific Computing information

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$15

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$57

How much do scientific computing jobs pay per hour?

As of Jul 30, 2026, the average hourly pay for scientific computing in New York is $34.44, according to ZipRecruiter salary data. Most workers in this role earn between $21.06 and $43.94 per hour, depending on experience, location, and employer.

What are the typical daily responsibilities of someone working in Scientific Computing?

Professionals in Scientific Computing typically spend their days developing and optimizing computational models, writing code to analyze large datasets, and running simulations on high-performance computing systems. They often collaborate closely with scientists, researchers, or engineers to interpret results and improve methodologies. Depending on the industry, they may also be responsible for documenting workflows, troubleshooting complex issues, and staying current with technological advances in their field. Daily work often involves problem-solving, technical meetings, and the continuous improvement of algorithms and computational processes.

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

To thrive in Scientific Computing, you need a strong background in mathematics, computer science, and scientific principles, often supported by a relevant degree such as physics, engineering, or computational science. Proficiency with programming languages like Python, C++, or MATLAB, experience with high-performance computing (HPC) systems, and familiarity with scientific software and libraries are typically essential. Excellent problem-solving abilities, teamwork, and clear communication skills are important soft skills for this role. These skills enable professionals to develop efficient computational solutions, collaborate effectively across multidisciplinary teams, and drive progress in research and innovation.

What is a Scientific Computing job?

A Scientific Computing job involves using advanced computational methods, algorithms, and mathematical modeling to solve complex scientific and engineering problems. Professionals in this field develop and optimize software, perform simulations, and analyze large datasets to support research in disciplines like physics, biology, and engineering. They often work with high-performance computing (HPC) systems and programming languages such as Python, C++, or Fortran. These roles are commonly found in academia, government research labs, and industries like aerospace, pharmaceuticals, and finance.

What are the most commonly searched types of Scientific Computing jobs in New York? The most popular types of Scientific Computing jobs in New York are:
What are popular job titles related to Scientific Computing jobs in New York? For Scientific Computing jobs in New York, the most frequently searched job titles are:
What job categories do people searching Scientific Computing jobs in New York look for? The top searched job categories for Scientific Computing jobs in New York are:
Scientific Computing jobs near you
Infographic showing various Scientific Computing job openings in New York as of July 2026, with employment types broken down into 92% Full Time, 7% Part Time, and 1% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $71,630 per year, or $34.4 per hour.

Data Scientist ::Onsite in NYC, NY (Onsite)

Talent Movers

New York, NY • On-site

Contractor

Re-posted 3 days ago

Job description

Title : Data Scientist

Location: Onsite in NYC, NY (Onsite)

Rate: ON C2C/W2

 

Top 3 must-have HARD skills:

Experience with hardware sensors and real-world data analysis
Direct experience working with biosensors or similar hardware, and analyzing the resulting data.
Signal processing expertise
Ability to process time domain signals and/or medical imaging systems, which is crucial for biosensor data.
Advanced programming and data manipulation
3+ years of hands-on experience with Python, R, MATLAB, or SQL for data extraction, manipulation, and visualization, including proficiency with scientific computing and analysis packages (NumPy, SciPy, Pandas, Scikit-learn, etc.).

Good to have skills:

Experience presenting findings from statistical and machine learning methods to diverse audiences.
Proficiency in data structures and algorithms.
Experience with data visualization libraries (Matplotlib, Pyplot, seaborn, ggplot2).
Experience working with large datasets.
Familiarity with scientific computing and analysis packages (dplyr, caret).
Advanced degree (Master’s or PhD) in computer science, statistics, neuroscience, biomedical engineering, or related field.

Job Description:

Summary:
The main function of the Data Scientist is to produce innovative solutions driven by exploratory data analysis from complex and high-dimensional datasets. The Data Scientist will contribute to biosensor data analysis and help to guide future biosensing R&D.
Job Responsibilities:
Execute, debug, and optimize distributed compute workflows for metric computation, analysis, and modeling across large datasets.
Apply knowledge of statistics, machine learning, programming, data modeling, simulation, and advanced mathematics to recognize patterns, identify opportunities, and make valuable discoveries leading to prototype biosensor development and product improvement.
Use a flexible, analytical approach to design, develop, and evaluate predictive models and advanced algorithms that lead to optimal value extraction from the biosensor data.
Generate and test hypotheses and analyze and interpret the results of product experiments.
Work with product engineers to translate prototypes into new products, services, and features and provide guidelines for large-scale implementation.
Leverage data visualization to help the team make decisions about future R&D directions to go.
Skills:
Experience with hardware sensors, and data analysis pertaining to real-world data.
Experience with signal processing pertaining to time domain signals and/or medical imaging systems
Experience presenting findings from statistical and machine learning methods to diverse audiences
Experience working with large datasets.
3+ years of experience performing data extraction, manipulation, and visualization using programming languages (e.g., Python), scientific computing languages (e.g., R, MATLAB), or SQL.
Proficiency in data structures and algorithms.
Experience with scientific computing and analysis packages such as NumPy, SciPy, Pandas, Scikit-learn, dplyr, caret.
Experience with data visualization libraries such as Matplotlib, Pyplot, seaborn, ggplot2.
Education/Experience:
Master of Science or PhD degree in computer science, statistics, neuroscience, biomedical engineering, or other relevant field.