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How much do computational data analytics jobs pay per hour?

As of Jul 21, 2026, the average hourly pay for computational data analytics in the United States is $54.75, according to ZipRecruiter salary data. Most workers in this role earn between $43.99 and $62.02 per hour, depending on experience, location, and employer.

What is computational data analysis?

Computational data analysis is a process used in data analytics roles to examine large datasets using algorithms, statistical models, and programming tools like Python or R. It involves cleaning, processing, and interpreting data to extract meaningful insights and support decision-making.

Which is better, DS or CS?

For a Computational Data Analytics role, both Data Science (DS) and Computer Science (CS) provide valuable skills; DS focuses on data analysis, modeling, and visualization, while CS emphasizes algorithms, programming, and software development. The choice depends on the specific job requirements and your career goals, but proficiency in programming languages like Python or R and understanding of data management are essential in both fields.

How does a Computational Data Analyst typically collaborate with cross-functional teams to deliver data-driven insights?

Computational Data Analysts frequently work alongside professionals from various departments, such as engineering, product management, and business strategy. They gather requirements, clarify analysis goals, and present findings in clear, actionable terms. Regular meetings and collaborative tools are often used to ensure alignment, while analysts translate complex data patterns into practical recommendations that support decision-making across the organization. This teamwork not only enhances the impact of their analyses but also provides valuable opportunities for learning and professional growth.

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

To thrive as a Computational Data Analytics professional, you need strong quantitative skills, proficiency in statistics, and expertise in data manipulation, typically supported by a degree in computer science, mathematics, or a related field. Familiarity with programming languages like Python or R, experience with data visualization tools (e.g., Tableau, Power BI), and knowledge of machine learning frameworks are commonly required. Excellent problem-solving abilities, effective communication, and the capacity to work collaboratively make candidates stand out. These skills enable professionals to extract actionable insights from complex datasets, drive informed decision-making, and add significant value to organizations.

Is 40 too late for data science?

Computational Data Analytics professionals can enter the field at any age, as success depends on skills, experience, and continuous learning. Many data scientists start or transition into the field later in life by acquiring relevant certifications, programming skills, and domain knowledge, making age less of a barrier than skill development and adaptability.

What is the difference between Computational Data Analytics vs Data Scientist?

AspectComputational Data AnalyticsData Scientist
Required CredentialsBachelor's or Master's in Data Science, Computer Science, or related fieldsBachelor's or Master's in Data Science, Computer Science, Statistics, or related fields
Work EnvironmentData analysis teams, research labs, tech companiesData analysis teams, research labs, tech companies
Employer & Industry UsageTech, finance, healthcare, academiaTech, finance, healthcare, academia
Common Search & ComparisonYesYes

Computational Data Analytics focuses on developing algorithms and computational methods to analyze large datasets, often emphasizing programming and algorithm design. Data Scientists combine statistical analysis, machine learning, and domain expertise to interpret data and generate insights. While both roles require similar educational backgrounds and work environments, Computational Data Analytics leans more toward algorithm development, whereas Data Scientists focus on modeling and interpretation.

What is computational data analytics?

Computational data analytics is the process of using computational methods, algorithms, and systems to analyze large and complex datasets. This field combines principles from computer science, mathematics, and statistics to extract meaningful insights and patterns from data. Professionals in computational data analytics use tools such as machine learning, data mining, and statistical modeling to solve real-world problems in various industries. Their work often involves programming, data visualization, and working with big data platforms.

What is the highest paying job in data analytics?

In data analytics, senior roles such as Data Science Director, Chief Data Officer, or Analytics Executive typically have the highest salaries, often exceeding six figures annually. These positions require advanced skills in machine learning, statistical analysis, and leadership, along with extensive experience and often advanced degrees or certifications.
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Computational Data Analytics jobs near you
Infographic showing various Computational Data Analytics job openings in the United States as of July 2026, with employment types broken down into 95% Full Time, 3% Part Time, and 2% Contract. Highlights an 80% Physical, 6% Hybrid, and 14% Remote job distribution, with an average salary of $113,873 per year, or $54.7 per hour.
Associate Staff - Computational Biologist

Associate Staff - Computational Biologist

MIT Lincoln Laboratory

Lexington, MA • On-site

Other

Medical, Dental, Vision, Retirement, PTO

Re-posted 14 days ago

Job description

Group 22-Counter Weapons of Mass Destruction (C-WMD) Systems Group. 

The Counter-WMD Systems Group at MIT Lincoln Laboratory is seeking a highly motivated and multidisciplinary biologist to support research and development efforts focused on national security challenges. We are looking for an individual with expertise in computational biology and data science who can contribute to our mission of developing advanced technologies to counter weapons of mass destruction

Job Description

Key Responsibilities:

  • Assist and / or lead projects involving the analysis of complex biological datasets, including next-generation sequencing and metagenomic data.
  • Apply state-of-the-art computational tools and algorithms, including machine learning and AI models, to biological questions related to multi-omics, immunology, and microbiome research.
  • Assist with laboratory experiments to generate and validate biological data.
  • Collaborate with a multidisciplinary team to solve broad and challenging problems in biodefense.

Required Qualifications:

  • Master's degree (or Bachelor's degree plus three years of work experience) in Bioengineering, Computational Biology, Bioinformatics, Molecular Biology, Data Science or a related field, or a Computer Science degree with extensive biology experience.
  • Expertise in computational biology and bioinformatics, with proficiency in programming languages such as Python, R, or similar.
  • Experience with state-of-the-art AI and machine learning approaches for biological data analysis.
  • Excellent problem-solving skills and the ability to work independently and in collaborative, multidisciplinary environments.
  • Experience designing, conducting, and interpreting the results of laboratory experiments
  • Effective written and verbal communication skills.
  • Ability to apply systems-level thinking to holistic biodefense solutions.
Valued Experience

Valued Experience:

  • High-performance computing, bioinformatics, and data analytics
  • Biosurveillance (e.g., epidemiology, physiological monitoring, environmental sampling)
  • Medical countermeasure / pharmaceutical development
  • Experience with genetic and/or protein language models
  • Willing to obtain and maintain a Top Secret level DoD security clearance

Recent Graduate Hiring Range: $116,400 - $140,000

Experienced Hiring Range: $116,400 - $182,200

 

Disclaimer: MIT Lincoln Laboratory provides a typical hiring range as a good faith estimate of what we reasonably expect to offer for this position at the time of posting. The final salary offered to a selected candidate will depend on various factors, including-but not limited to-the scope and responsibilities of the role, the candidate's experience, skills and education/training, internal equity considerations and applicable legal requirements. This range reflects base salary only and does not include additional forms of compensation or benefits.

At MIT Lincoln Laboratory, our exceptional career opportunities include many outstanding benefits to help you stay healthy, feel supported, and enjoy a fulfilling work-life balance. Benefits offered to employees include: 

  • Comprehensive health, dental, and vision plans
  • MIT-funded pension
  • Matching 401K
  • Paid leave (including vacation, sick, parental, military, etc.)
  • Tuition reimbursement and continuing education programs
  • Mentorship programs
  • A range of work-life balance options
  • ... and much more!  

Please visit our Benefits page for more information. As an employee of MIT, you can also take advantage of other voluntary benefits, discounts and perks.

Selected candidate will be subject to a pre-employment background investigation and must be able to obtain and maintain a Secret level DoD security clearance.

MIT Lincoln Laboratory is an Equal Employment Opportunity (EEO) employer. All qualified applicants will receive consideration for employment and will not be discriminated against on the basis of race, color, religion, sex, sexual orientation, gender identity, national origin, age, veteran status, disability status, or genetic information; U.S. citizenship is required.

 

Requisition ID: 42991 

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