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Computational Data Science Jobs in Virginia (NOW HIRING)

Guidehouse

Senior Data Scientist

Chantilly, VA

S./M.A. in Data Science/Analytics, Statistics, Mathematics, Operations Research, Computer Science, Information Systems, Engineering, Economics, or similar quantitative/computational discipline.

Leidos

Senior Data Scientist

Alexandria, VA · Hybrid

$131K - $237K/yr

As a Senior Data Scientist, you will : * Lead the design, development, and deployment of advanced ... Science, Mathematics, Statistics, Engineering, Physics, Computational Social Science, etc.

Virginia Tech

Computational Scientist

Blacksburg, VA

Computational Scientist Apply now Back to search results Job no: 536897 Work type: Administrative ... Exposure to data intensive or big data research workflows. Preferred Qualifications Proven record ...

Noblis

Data Scientist and Instructor

Springfield, VA · On-site

... Computational Thinking, Programming, Statistics, or Data Visualization). * 10 years of experience focusing on the concepts and applications of data analytics, computer science and programming, data ...

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Computational Data Science information

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$16

$56

$80

How much do computational data science jobs pay per hour?

As of Jul 21, 2026, the average hourly pay for computational data science in Virginia is $56.33, according to ZipRecruiter salary data. Most workers in this role earn between $46.25 and $66.73 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.
What are popular job titles related to Computational Data Science jobs in Virginia? For Computational Data Science jobs in Virginia, the most frequently searched job titles are:
What job categories do people searching Computational Data Science jobs in Virginia look for? The top searched job categories for Computational Data Science jobs in Virginia are:
What cities in Virginia are hiring for Computational Data Science jobs? Cities in Virginia with the most Computational Data Science job openings:
Computational Data Science jobs near you
Senior Data Scientist

Senior Data Scientist

Guidehouse

Chantilly, VA

Full-time

Medical, Dental, Vision, Life, Retirement

Re-posted 6 days ago

Guidehouse rating

7.5

Company rating: 7.5 out of 10

Based on 26 frontline employees who took The Breakroom Quiz

37th of 58 rated business consultants

Job description

Job Family:

Data Science Consulting


Travel Required:

None


Clearance Required:

Active Top Secret SCI with Polygraph

What You Will Do:
Our Data and Analytics consultants help clients maximize the value of their data. This high performing team works with clients to implement the full spectrum of data analytics and data science, from data querying and data wrangling to data visualization and dashboarding for business intelligence (BI), to predictive analytics, machine learning, and artificial intelligence. They help clients define their information strategy, architecture, and governance, get the most value from business intelligence and analytics, and implement enterprise content and data management solutions to enable business insights, reduce cost and complexity, increase trust and integrity, and improve operational effectiveness.

The successful candidate will bring expertise in developing, building, and maintaining data assets and managing a team. This is a high visibility role and the candidate will be expected to speak confidently and intelligently about a variety of data products, methodologies, industry trends and challenges. This role will be involved in managing and maintaining client relationships as well as proactively participate in business development discussions. The candidate should demonstrate the flexibility to pivot and respond quickly to a dynamic and evolving company culture and broader energy transition landscape.

Duties will include:

  • Coordinating and leading internal team actions to meet project and client objectives.

  • Consulting with the client to determine analytics required, technical solutions and methods to ensure a high confidence model for client decision making.

  • Interfacing with Client Subject Matter Experts to design, develop, validate and deploy capabilities that enable client objectives.

What You Will Need:

  • An ACTIVE and MAINTAINED TS/SCI Federal or DoD security clearance with a FULL SCOPE (FS/FSP) polygraph.

  • Bachelor's degree.

  • THREE (3) or more years of experience in Data Science, Data Analytics, and/or Data Visualization.

  • Experience cleaning, manipulating, and pre-processing data using Python, SQL, R, and/or Tableau Prep Builder.

  • Experience developing reports and dashboards for business intelligence, utilizing Data Visualization tools such as Tableau.

What Would Be Nice to Have:

  • M.S./M.A. in Data Science/Analytics, Statistics, Mathematics, Operations Research, Computer Science, Information Systems, Engineering, Economics, or similar quantitative/computational discipline.

  • Tableau Desktop Certification: Certified Professional, Certified Associate, Specialist. Tableau Server Certification: Certified Professional, Certified Associate.

  • Proficiency querying data in SQL.

  • Experience performing data science / analytics, such as statistical modelling, predictive analysis, or machine learning using Python or R.

  • Experience with MS Forms and Power Automate.

  • Ability to support clients in identifying and addressing needs, building relationships, and driving solutions forward and experience leading small teams.

  • Excellent communication skills, both verbal and written.

#LI-DNI


What We Offer:

Guidehouse offers a comprehensive, total rewards package that includes competitive compensation and a flexible benefits package that reflects our commitment to creating a diverse and supportive workplace.

Benefits include:

  • Medical, Rx, Dental & Vision Insurance

  • Personal and Family Sick Time & Company Paid Holidays

  • Position may be eligible for a discretionary variable incentive bonus

  • Parental Leave and Adoption Assistance

  • 401(k) Retirement Plan

  • Basic Life & Supplemental Life

  • Health Savings Account, Dental/Vision & Dependent Care Flexible Spending Accounts

  • Short-Term & Long-Term Disability

  • Student Loan PayDown

  • Tuition Reimbursement, Personal Development & Learning Opportunities

  • Skills Development & Certifications

  • Employee Referral Program

  • Corporate Sponsored Events & Community Outreach

  • Emergency Back-Up Childcare Program

  • Mobility Stipend

About Guidehouse

Guidehouse is an Equal Opportunity Employer-Protected Veterans, Individuals with Disabilities or any other basis protected by law, ordinance, or regulation.

Guidehouse will consider for employment qualified applicants with criminal histories in a manner consistent with the requirements of applicable law or ordinance including the Fair Chance Ordinance of Los Angeles and San Francisco.

If you have visited our website for information about employment opportunities, or to apply for a position, and you require an accommodation, please contact Guidehouse Recruiting at 1-571-633-1711 or via email at RecruitingAccommodation@guidehouse.com. All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodation.

All communication regarding recruitment for a Guidehouse position will be sent from Guidehouse email domains including @guidehouse.com or guidehouse@myworkday.com. Correspondence received by an applicant from any other domain should be considered unauthorized and will not be honored by Guidehouse. Note that Guidehouse will never charge a fee or require a money transfer at any stage of the recruitment process and does not collect fees from educational institutions for participation in a recruitment event. Never provide your banking information to a third party purporting to need that information to proceed in the hiring process.

If any person or organization demands money related to a job opportunity with Guidehouse, please report the matter to Guidehouse's Ethics Hotline. If you want to check the validity of correspondence you have received, please contact recruiting@guidehouse.com. Guidehouse is not responsible for losses incurred (monetary or otherwise) from an applicant's dealings with unauthorized third parties.

Guidehouse does not accept unsolicited resumes through or from search firms or staffing agencies. All unsolicited resumes will be considered the property of Guidehouse and Guidehouse will not be obligated to pay a placement fee.

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