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Computational Data Analytics Jobs (NOW HIRING)

TestingXperts

Big Data Analytics Process

Houston, TX · On-site

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

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 ...

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 · On-site

$71K - $98K/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

$71K - $98K/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 ...

Transcripta Bio

Computational Biologist

Palo Alto, CA · On-site

Analyze data from drug perturbation screens to identify transcriptomic signatures, compound-gene ... PhD in Bioinformatics, Computational Biology, Genomics, or a related field with 3+ years of ...

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How much do computational data analytics jobs pay per hour?

As of Jun 25, 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.

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. Age is less important than your ability to adapt and develop expertise in tools like Python, R, and SQL.

Will AI replace data analysts?

AI tools can automate routine data processing and analysis tasks, but data analysts are essential for interpreting complex insights, making strategic decisions, and applying domain knowledge. The role of a data analyst involves skills like critical thinking, communication, and understanding business context, which are difficult for AI to fully replicate. Therefore, AI is more likely to augment rather than replace data analysts in the foreseeable future.

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.

Is data analytics a high paying job?

Data analytics is generally considered a well-paying field, especially for roles like computational data analysts who possess strong skills in programming, statistics, and data visualization tools. Salaries tend to increase with experience, certifications, and advanced technical expertise, making it a lucrative career option in the tech industry.

What field is the highest paid data analyst?

Data analysts working in finance, investment banking, and technology tend to have the highest salaries, especially those with advanced skills in machine learning, statistical analysis, and proficiency in tools like SQL and Python. Specializing in these high-demand industries and obtaining relevant certifications can lead to higher compensation.
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 June 2026, with employment types broken down into 17% Full Time, 10% Part Time, 66% Contract, and 7% 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

Other

Posted yesterday

Job description

Big Data Analytics Process

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.

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

· The data scientist role will support Information Technology (IT) team to engage with business stakeholders on their advanced analytics requirements.

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