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Computational Data Analytics Jobs in Virginia (NOW HIRING)

Seeking a Data Scientist to engage in high-level analytical projects for government initiatives in ... graphics, computational models, and comprehensive analyses to both internal and external ...

... e., Computational Thinking, Programming, Statistics, or Data Visualization). * Minimum 5 years of experience focusing on the concepts and applications of data analytics, computer science and ...

Utilize analytical, statistical, and programming skills to collect, analyze, and interpret large ... and computational methods. * Develop and/or consult on advanced methodological approaches ...

Utilize analytical, statistical, and programming skills to collect, analyze, and interpret large ... and computational methods. * Develop and/or consult on advanced methodological approaches ...

Utilize advanced tools and computational skills to interpret, connect, predict, and make discoveries in complex data * Apply machine learning, algorithm analysis, and data clustering techniques to ...

... computational programming, and practical problem solving, while clearly explaining technical ... Develop advanced analytics, AI, and data science solutions to solve complex business and technical ...

Utilize advanced tools and computational skills to interpret, connect, predict, and make discoveries in complex data * Apply machine learning, algorithm analysis, and data clustering techniques to ...

Providing support to the Sponsor's business analytics stakeholders whenever needed. * Apply AI and ... Systems, or Computational Linguistics. * A strong background in data analysis, with a strong ...

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Computational Data Analytics information

See Virginia salary details

$24

$54

$93

How much do computational data analytics jobs pay per hour?

As of Jun 15, 2026, the average hourly pay for computational data analytics in Virginia is $54.28, according to ZipRecruiter salary data. Most workers in this role earn between $43.61 and $61.49 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.
What are popular job titles related to Computational Data Analytics jobs in Virginia? For Computational Data Analytics jobs in Virginia, the most frequently searched job titles are:
What job categories do people searching Computational Data Analytics jobs in Virginia look for? The top searched job categories for Computational Data Analytics jobs in Virginia are:
Infographic showing various Computational Data Analytics job openings in Virginia as of June 2026, with employment types broken down into 100% Full Time. Highlights an 92% In-person, and 8% Remote job distribution, with an average salary of $112,896 per year, or $54.3 per hour.

Data Scientist

Novul Solutions

Herndon, VA • On-site

Full-time

Medical, Dental, Vision, Retirement, PTO

Posted 16 hours ago


Job description

Job Description
Seeking a Data Scientist to engage in high-level analytical projects for government initiatives in Herndon, VA. This role demands the development and communication of strategic graphics, computational models, and comprehensive analyses to both internal and external stakeholders.
Key Responsibilities:
  • Develop strategic analytic products summarizing data analysis methods and results.
  • Deliver sophisticated briefings on technical analytic projects.
  • Provide complex and timely data analysis supporting key objectives.
  • Employ optimal research designs for data collection and analysis.
  • Acquire, process, and refine large or complex data sets, utilizing programming as needed.

Requirements
  • Expertise in applied mathematics, computer programming, and visualization.
  • Proficiency in cloud service metrics analysis and cloud vendor performance.
  • Ability to organize information with multiple data management tools.
  • Skill in translating technical findings into accessible narratives.
  • Bachelor's Degree in a quantitative or technical field.

Highly Desired:
  • Experience in the Sponsor's domain and with business operations.
  • Knowledge of cloud computing (IaaS, PaaS, SaaS).
  • Background in or with the Department of Defense.
  • Relevant certifications in quantitative fields or Data Science

Benefits
Paid Time and Flexibility
  • Paid Time Off (PTO): Enjoy up to 10 paid days off plus an additional 5 floating days each year, offering flexibility and work-life balance.
  • Holidays: Benefit from 11 paid holidays, with the option to use flex time instead, accommodating personal preferences and needs.
  • Flexibility in Work Hours: Tailored to support work-life balance, enhancing employee satisfaction and productivity.

Financial and Retirement Benefits
  • Bi-Monthly Payroll: Consistent and reliable pay schedule, ensuring financial stability.
  • Retirement Savings Plan (401[k]): A partnership with one of the top retirement plan providers in the U.S., featuring a guaranteed 3% match, fostering long-term financial security. Eligibility criteria include being 21 years or older, with plan participation starting after 3 months of employment.
  • Performance and Recognition Awards: Quarterly individual or company-wide awards, acknowledging and rewarding excellence.

Health and Wellness
  • UnitedHealthcare PPO Plan: Comprehensive national coverage, including medical, dental, vision, and Health Savings Account (HSA) options. Coverage begins on the first of the month following your start date. Enrollment must be completed within 30 days of starting to avoid waiting for the annual enrollment period in October.

Career Development and Commuter Support
  • Career Advancement: Offers reimbursement for tuition and training essential for career growth, promoting continuous learning and development.
  • Commuter Benefits: A $150 monthly contribution towards parking expenses, easing the commute. Receipts are required by the 25th of each month, with reimbursements processed in the following payroll.

Bonus Programs
  • Performance-Based Bonuses: Project-specific bonuses that reward individual contributions to the company's success.

Annual Company-Wide Bonus: Reflects the company's overall performance, sharing success across the team.