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Applications Scientist Jobs in Virginia (NOW HIRING)

Analygence

Data Scientist

Arlington, VA · On-site

Tharros is seeking a Data Scientist to serve as the program's senior analytical authority, leading ... Lead development of Mission Assurance analytical applications within Palantir Foundry, including ...

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How much do applications scientist jobs pay per hour?

As of Sep 5, 2026, the average hourly pay for applications scientist in Virginia is $52.19, according to ZipRecruiter salary data. Most workers in this role earn between $41.92 and $60.05 per hour, depending on experience, location, and employer.

What is an applications scientist?

Applications Scientists are professionals who bridge the gap between scientific research and product development by providing technical support, training, and solutions to customers using scientific instruments or software. They work closely with sales, marketing, and research teams to demonstrate how products can be applied to solve specific problems in various industries, such as biotechnology, pharmaceuticals, or materials science. Their role often includes conducting product demonstrations, troubleshooting issues, and offering technical expertise to ensure customer success.

What are the key skills and qualifications needed to thrive as an applications scientist?

To thrive as an Applications Scientist, you need a strong background in scientific research, data analysis, and product/application expertise, often supported by a degree in chemistry, biology, or a related field. Familiarity with laboratory instrumentation, specialized software (such as chromatography or spectroscopy programs), and sometimes relevant certifications are typically required. Excellent communication, problem-solving abilities, and customer-focused interpersonal skills help you translate technical information and support clients effectively. These skills ensure you can bridge the gap between product development and end-users, driving customer satisfaction and successful product adoption.

What are some common challenges applications scientists face when working with customers on integrating new technologies?

Applications Scientists often encounter challenges such as bridging the gap between complex technical capabilities and the specific needs of end-users. They must translate scientific principles into practical solutions, address unforeseen technical hurdles during product integration, and provide clear documentation and training. Effective communication and adaptability are crucial, as they frequently collaborate with cross-functional teams—including R&D, sales, and customer support—to ensure successful product adoption and user satisfaction.

What is the difference between Applications Scientist vs Product Specialist?

AspectApplications ScientistProduct Specialist
Required credentialsTypically requires a degree in life sciences, chemistry, or related fields; often a master's or PhDUsually holds a degree in science or engineering; certifications may enhance credibility
Work environmentLaboratory, customer sites, or corporate R&DCustomer-facing, sales, and technical support settings
Employer and industry usageBiotech, pharma, and scientific instrument companiesInstrument and equipment manufacturers, biotech firms

Applications Scientists and Product Specialists often collaborate but focus on different aspects. Applications Scientists primarily support product development and technical validation, while Product Specialists focus on customer engagement and sales support. Both roles require scientific expertise but serve distinct functions within the industry.

Do you need a PhD to be an Applications Scientist?

A PhD is often preferred for Applications Scientist roles, especially in research-intensive fields, but many positions also accept candidates with a master's degree or relevant industry experience. Strong technical knowledge, problem-solving skills, and familiarity with laboratory tools or software are important for this role.

What is the average salary for an applications scientist?

The average salary for an applications scientist typically ranges from $70,000 to $110,000 annually, depending on experience, education, and industry. Senior roles or those with specialized skills in data analysis or laboratory techniques may earn higher compensation.

What are popular job titles related to Applications Scientist jobs in Virginia?

For Applications Scientist jobs in Virginia, the most frequently searched job titles are:

What job categories do people searching Applications Scientist jobs in Virginia look for?

The top searched job categories for Applications Scientist jobs in Virginia are:

Applications Scientist jobs near you
Infographic showing various Applications Scientist job openings in Virginia as of August 2026, with employment types broken down into 1% As Needed, 80% Full Time, 16% Part Time, 1% Temporary, and 2% Contract. Highlights an 88% Physical, 3% Hybrid, and 9% Remote job distribution, with an average salary of $108,551 per year, or $52.2 per hour.

Data Scientist

Science Applications International Corporation

Chantilly, VA

Full-time

Re-posted 4 days ago

SAIC rating

7.6

Company rating: 7.6 out of 10

Based on 81 frontline employees who took The Breakroom Quiz

103rd of 226 rated it services

Job description

SAIC is hiring a Data Scientist to deliver Systems Engineering Technical Advisor (SETA) support a program based in Chantilly, VA. This role will contribute to the National Reconnaissance Office's (NRO) Ground Enterprise Directorate (GED), which oversees the acquisition and lifecycle management of systems from inception to deployment and operations.

As the Data Scientist you will support the analysis of complex data to drive strategic mission efforts. The role supports the resolution of operational and systems problems into data-driven solutions, guides analytic strategy, and advises leadership on mission impact, model risk, and data-informed tradeoffs.

Job Responsibilities to include:

  • Supports designing and managing data sets to ensure efficient data flow and interoperability with existing and emerging programs.
  • Supports the collection and integration of large, complex data sets that meet cross-organizational requirements.
  • Evaluates data quality, reliability, and efficiency throughout the data lifecycle.
  • Collaborating with other data scientists, software developers, operators, project managers, and clients to prepare data for predictive modeling.
  • Documents internal process improvements to optimize data delivery and automate manual processes.
  • Supports testing and validation procedures to ensure operational platforms function correctly, including the ability to gather user feedback, identify issues, conduct updates, and perform routine quality assurance checks.
  • Supports the development of essential technical documentation for reference and reporting, which includes documenting processes, system specifications, and modifications.
  • Supports data compliance with regulations, develop guidance, and promote ethical use of developed platforms, data repositories, and relevant technical records.
SAIC is a premier mission integrator focused on advancing the power of technology and innovation to serve and protect our world. Our robust portfolio of offerings across the defense, space, intelligence, and civilian markets includes secure high-end solutions in mission IT, enterprise IT, engineering services, and professional services. We integrate emerging technology, rapidly and securely, into mission critical operations that modernize and enable critical national imperatives.

We are approximately 23,000 strong; driven by mission, united by purpose, and inspired by opportunities. SAIC is an Equal Opportunity Employer. Headquartered in Reston, Virginia, SAIC has annual revenues of approximately $7.3 billion. For more information, visit saic.com. For ongoing news, please visit our newsroom.

Required Education and Experience:

  • Bachelors and nine (9) years or more experience; Masters and seven (7) years or more experience ; PhD or JD and four (4) years or more experience. Relevant experience to be substituted in lieu of degree. 
  • 5+ years of experience in software engineering with IC, DoD, and/or commercial space architectures, systems, and/or operations.
  • Hands-on practical experience with data analytics, machine learning, and statistical methods.
  • Experience in applying modern techniques in artificial intelligence (AI), data science, machine learning (ML), or statistics.
  • Demonstrated high level of initiative, creative problem-solving, and critical thinking.
  • Demonstrated capability and success working in team environments.
  • Strong oral and written communications ability on significant technical matters often requiring coordination within a high tempo environment.
  • Good working knowledge of MS Office applications.

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