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Computational Data Analytics Jobs (NOW HIRING)

TestingXperts

Big Data Analytics Process

Houston, TX · On-site

... computational methods Strong skills in communicating and presenting data-derived insights to non ... Analytics Uses cases. 2. Processing, cleansing, and verifying the integrity of data used for ...

Corning

Scientist, Data Analytics

Corning, NY

$71.34K - $98.09K/yr

The incumbent will act as a subject matter expert within a team environment to provide data analytics; this may require the creation of novel computational methods and analytical models. Day to Day ...

Genedata

Technical Sales Engineer

Lexington, MA · On-site

... or computational data, ideally in a life sciences or biopharma context • Proven experience in data engineering, and analysis, particularly with pharmaceutical R&D data (experience with data ...

Corning

Scientist, Data Analytics

Corning, NY

$71.34K - $98.09K/yr

The incumbent will act as a subject matter expert within a team environment to provide data analytics; this may require the creation of novel computational methods and analytical models. Day to Day ...

Corning

Scientist, Data Analytics

Corning, NY · On-site

$71.34K - $98.09K/yr

The incumbent will act as a subject matter expert within a team environment to provide data analytics; this may require the creation of novel computational methods and analytical models. Day to Day ...

Bruker Corporation

Computational Biologist

$101K - $156K/yr

Overview Computational Biologist - Technical Support, Spatial Biology Bruker Spatial Biology is ... In this role, you will support data analysis for Bruker's spatial biology platforms. You will ...

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How much do computational data analytics jobs pay per hour?

As of Jun 4, 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 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.

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 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 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.

More about Computational Data Analytics jobs
What cities are hiring for Computational Data Analytics jobs? Cities with the most Computational Data Analytics job openings:
What states have the most Computational Data Analytics jobs? States with the most job openings for Computational Data Analytics jobs include:
What job categories do people searching Computational Data Analytics jobs look for? The top searched job categories for Computational Data Analytics jobs are:
Computational Data Analytics jobs near you
Infographic showing various Computational Data Analytics job openings in the United States as of May 2026, with employment types broken down into 96% Full Time, 2% Part Time, and 2% Nights. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $113,873 per year, or $54.7 per hour.
Big Data Analytics Process

Big Data Analytics Process

TestingXperts

Houston, TX • On-site

Full-time

Posted 24 days ago

Job description

Company Description

Greetings for the day!
My name is Suneetha from Testing Xperts, we are a global staffing, consulting and technology solutions company, offering industry-specific solutions to our fortune 500 clients and worldwide corporations.

Thanks & Regards,

Suneetha. G

+1 631-759-8044 EXT 303 (O)

+1 347-826-3427 (F)

Job Description

Role: Big Data Analytics Process

Location: Houston, TX

Job Description:

Must Have Skills (Top 2 technical skills only)
Minimum 8 years of relevant experience in applying data mining, artificial intelligence, signal processing, machine learning, optimization etc. in business analytics or scientific/engineering settings

Experience with statistical software, scripting languages, tools, and platforms (e.g., R, Python, Hadoop etc.)

Nice to have skills (Top 2 only)
A demonstrated ability to solve challenging business problems using a data science approach by developing novel and/or adapting existing computational methods

Strong skills in communicating and presenting data-derived insights to non-technical audiences appropriately.

Desired years of experience : 8+ Years

Education/ Certifications (Required) : Masters or Ph.D. in Mathematics, Statistics, Computer Science, Operations Research, Engineering Science.

Top 3 responsibilities you would expect the subcon to shoulder and execute:
1. Collaborate with business users to identify, elaborate and prioritize Analytics Uses cases.
2. Processing, cleansing, and verifying the integrity of data used for analysis
3. Apply analytical rigor and statistical methods to analyze large amounts of data, using advanced analytics techniques. And, presenting data insights using high impact visualization

Will the candidate be client facing and/or working with business users? Yes

What is the team size, make up, culture, soft skills, and dress code, Hours?
The data scientist role will support Information Technology (IT) team to engage with business stakeholders on their advanced analytics requirements.

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Additional Information

All your information will be kept confidential according to EEO guidelines.

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