ZipRecruiter

Log In

1

Computational Data Science Jobs (NOW HIRING)

IMAGINEEER LLC

Scientific Data Analyst

Arlington, VA · On-site

$110K - $115K/yr

In this role, you will provide computational, data science, and bioinformatics support for Office of Research Innovation, Validation, and Application's (ORIVA) research validation and application ...

Imagineeer LLC

Scientific Data Analyst

Arlington, VA · On-site

$110K - $115K/yr

In this role, you will provide computational, data science, and bioinformatics support for Office of Research Innovation, Validation, and Application's (ORIVA) research validation and application ...

Adidev Technologies Inc

Data Science

San Francisco, CA · Remote

As a Data Scientist/Data Science Specialist for Adidev Technologies Inc., you will be enhancing and ... S. in Computer Science, Computational Physics, Operations Research, Geospatial Sciences, Remote ...

Adidev Technologies Inc

Data Science

San Francisco, CA · On-site

As a Data Scientist/Data Science Specialist for Adidev Technologies Inc., you will be enhancing and ... S. in Computer Science, Computational Physics, Operations Research, Geospatial Sciences, Remote ...

1872 Consulting

Data Science Manager

Santa Clara, CA

Establish operational objectives and work plans for the Data Science/Computational Linguistics group that meet the strategic objectives of the AI team. * Lead projects requiring collaboration across ...

next page

Showing results 1-20

All JobsComputational Data Science Jobs

Computational Data Science information

See salary details

$16

$56

$81

How much do computational data science jobs pay per hour?

As of Jul 30, 2026, the average hourly pay for computational data science in the United States is $56.81, according to ZipRecruiter salary data. Most workers in this role earn between $46.63 and $67.31 per hour, depending on experience, location, and employer.

What does a computational data scientist do?

A computational data scientist analyzes large datasets using programming languages like Python or R, develops algorithms, and applies statistical models to extract insights and solve complex problems. They often work with machine learning tools and require strong analytical skills, programming knowledge, and familiarity with data management environments.

Is computational science in demand?

Computational Data Science is in high demand across industries such as technology, finance, healthcare, and research, driven by the increasing reliance on data analysis, machine learning, and big data tools. Professionals with skills in programming, statistical analysis, and data modeling are sought after for roles involving data-driven decision making and automation.

What is the difference between Computational Data Science vs Data Analyst?

AspectComputational Data ScienceData Analyst
Required CredentialsTypically requires a degree in Computer Science, Data Science, or related fields; often includes programming certificationsUsually requires a degree in Statistics, Business, or related fields; may include basic data analysis certifications
Work EnvironmentInvolves programming, modeling, and developing algorithms; often in tech or research settingsFocuses on interpreting data, creating reports, and supporting decision-making; in business or corporate environments
Employer & Industry UsageUsed in tech companies, research institutions, and industries requiring advanced modelingCommon in finance, marketing, healthcare, and business sectors

Computational Data Science involves advanced programming, algorithm development, and modeling, often in technical environments. Data Analysts focus on interpreting data, generating reports, and supporting business decisions. While both roles work with data, Computational Data Scientists typically require stronger programming skills and work on building models, whereas Data Analysts focus on data interpretation and visualization.

What is Computational Data Science?

Computational Data Science is an interdisciplinary field that combines computer science, statistics, and domain knowledge to extract insights and knowledge from complex data sets using computational techniques. Professionals in this field use algorithms, machine learning, and advanced analytics to solve real-world problems by processing and interpreting large volumes of data. The work often involves programming, data modeling, and visualization, making it crucial in industries such as healthcare, finance, and technology. Computational Data Scientists help organizations make data-driven decisions and innovate through predictive modeling and data analysis.

Is 40 too late for data science?

Computational Data Science is a field where individuals can enter at any age, as success depends on skills, experience, and continuous learning. Many professionals transition into data science later in their careers by acquiring relevant knowledge in programming, statistics, and machine learning through online courses or certifications. Age is generally not a barrier if you develop the necessary technical skills and stay current with industry tools.

What are some common challenges faced by computational data scientists when working on cross-functional teams?

Computational data scientists often collaborate closely with professionals from diverse backgrounds, such as software engineers, domain experts, and business stakeholders. One common challenge is translating complex technical findings into actionable insights for non-technical team members. Additionally, aligning project goals and expectations across disciplines can require extra communication and flexibility. Overcoming these challenges often involves developing strong interpersonal skills, proactively clarifying requirements, and fostering a collaborative team culture.

What are the key skills and qualifications needed to thrive as a Computational Data Scientist, and why are they important?

To thrive as a Computational Data Scientist, you need a strong background in mathematics, statistics, programming (especially Python or R), and data analysis, often supported by a relevant degree in computer science, statistics, or a related field. Proficiency with data manipulation tools (like Pandas, NumPy), machine learning frameworks (such as TensorFlow or Scikit-learn), and cloud computing platforms is highly valued, along with experience using data visualization tools. Critical thinking, problem-solving, communication, and collaboration skills make someone stand out in this role. These abilities are crucial for extracting actionable insights from complex data, building effective models, and communicating findings to drive informed business decisions.

What is the highest paid job in data science?

The highest paid roles in data science are often senior positions such as Lead Data Scientist, Machine Learning Director, or Chief Data Officer, with salaries exceeding $150,000 annually. These roles typically require advanced skills in machine learning, big data tools, and leadership experience. Compensation varies by industry, location, and company size.
More about Computational Data Science jobs
What cities are hiring for Computational Data Science jobs? Cities with the most Computational Data Science job openings:
What states have the most Computational Data Science jobs? States with the most job openings for Computational Data Science jobs include:
What job categories do people searching Computational Data Science jobs look for? The top searched job categories for Computational Data Science jobs are:
Computational Data Science jobs near you
Infographic showing various Computational Data Science job openings in the United States as of July 2026, with employment types broken down into 2% Locum Tenens, 66% Full Time, 31% Part Time, and 1% Contract. Highlights an 65% Physical, 2% Hybrid, and 33% Remote job distribution, with an average salary of $118,171 per year, or $56.8 per hour.

Computational Data Scientist II

University of Pittsburgh

Pittsburgh, PA • On-site

Full-time

Posted 8 days ago

Job description

The Bioinformatics Core within the Division of Health Informatics at UPMC Children's Hospital of Pittsburgh is seeking a computational biologist or data scientist to develop and apply machine learning and deep learning methods for omics-driven biomedical research. This individual will work closely with faculty and collaborators across multiple pediatric research programs to support biologically grounded, translationally relevant research. Equivalent relevant work experience may be substituted for degree requirement. This position is located at UPMC Children's Hospital of Pittsburgh in Lawrenceville. PA Child Abuse History Clearance, PA State Police Criminal Record Check, and FBI Criminal Record Check will be required prior to the start of employment. Also, a current TB test will be required as a condition of employment. EEO/AA/M/F/Vets/Disabled.
Minimum Qualifications
Applicants should have an MS or PhD in computational biology, bioinformatics, computer science, statistics, data science, biomedical informatics, or a related quantitative field.
The successful candidate should have strong programming skills in Python and/or R, with experience using libraries such as PyTorch, TensorFlow, scikit-learn, or comparable tools. Experience in applying computational or statistical modeling to biomedical or biological datasets is expected.
Prior experience working with single-cell, spatial omics, or related high-dimensional omics datasets is highly desirable. Candidates should be strong critical thinkers who can translate ideas into completed analyses, models, or tools; manage contributions across multiple collaborative research projects; work independently and as part of multidisciplinary teams; and demonstrate strong oral and written communication skills.
Preferred qualifications include:
• Demonstrated experience designing and implementing models for high-dimensional biological data, beyond routine application of existing analysis pipelines.
• Hands-on experience with graph neural networks or perturbation modeling.
• Experience integrating omics data with clinical data sources such as electronic health records (EHR).
• Evidence of independent technical contribution, such as first-author or co-author publications, preprints, conference presentations, open-source software, deployed tools, analytical pipelines, or a relevant project portfolio.

Apply