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Data Science Engineer Jobs in Alexandria, VA (NOW HIRING)

Integral

Cybersecurity Lead

Picatinny Arsenal, NJ · On-site

Collect data to support reporting and IA management activities across the investment life cycle ... Bachelor's Degree in Computer Science or similar Information Technology Field. * 7 years ...

Peraton

Data Science Specialist

Mclean, VA · On-site

$146K - $234K/yr

The Data Science Specialist will leverage technical expertise in software engineering, data analysis, data integration, and data modeling to develop innovative analytic capabilities supporting ...

Peraton

Data Science Specialist

Mclean, VA · On-site

$146K - $234K/yr

The Data Science Specialist will leverage technical expertise in software engineering, data analysis, data integration, and data modeling to develop innovative analytic capabilities supporting ...

Peraton

Data Science Specialist

Mclean, VA · On-site

$146 - $234/hr

The Data Science Specialist will leverage technical expertise in software engineering, data analysis, data integration, and data modeling to develop innovative analytic capabilities supporting ...

Deloitte

Generative AI Data Engineer III

Washington, DC · On-site

$129K - $155K/yr

Work you'll do As an AI and Data Science Engineer III on the team, you will be responsible for: * Design, build, test, and deploy machine learning and artificial intelligence solutions for business ...

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Showing results 21-40

All JobsData Science Engineer JobsData Science Engineer Jobs in Alexandria, VA

Data Science Engineer information

See Alexandria, VA salary details

$47.6K

$138.8K

$190K

How much do data science engineer jobs pay per year?

As of Sep 6, 2026, the average yearly pay for data science engineer in Alexandria, VA is $138,837.00, according to ZipRecruiter salary data. Most workers in this role earn between $122,600.00 and $147,200.00 per year, depending on experience, location, and employer.

What is a data science engineer?

A Data Science Engineer is a professional who bridges the gap between data science and software engineering. They focus on designing, building, and maintaining scalable data pipelines, infrastructure, and machine learning models for production use. Their role involves data preprocessing, model deployment, performance optimization, and integrating AI solutions into applications. They work closely with data scientists, software engineers, and DevOps teams to ensure efficient data workflows.

What are the typical daily responsibilities of a data science engineer?

Data Science Engineers typically spend their days designing and building data pipelines, preparing and cleaning large datasets, and developing machine learning models to solve business problems. They work closely with data scientists, software engineers, and business stakeholders to translate requirements into scalable technical solutions. Responsibilities also include deploying models to production, monitoring their performance, and iterating on solutions based on feedback. This role offers a dynamic mix of coding, data analysis, and teamwork, making each day varied and intellectually engaging.

What are the key skills and qualifications needed to thrive in the data science engineer position, and why are they important?

A Data Science Engineer should have a strong background in statistics, machine learning, programming (typically Python or R), and data engineering, often supported by a degree in computer science, engineering, or a related field. Familiarity with data processing frameworks (like Spark or Hadoop), cloud platforms (AWS, GCP, or Azure), and certifications in data science or cloud technology are highly valued. Excellent problem-solving skills, communication abilities, and collaboration are essential soft skills for working effectively in cross-functional teams. These competencies enable Data Science Engineers to build scalable data solutions, deliver actionable insights, and drive business impact.

What does a data science engineer do?

A data science engineer designs, develops, and maintains data pipelines and infrastructure to support data analysis and machine learning models. They work with large datasets, use programming languages like Python or Scala, and often collaborate with data scientists and software engineers to implement scalable data solutions.

What are popular job titles related to Data Science Engineer jobs in Alexandria, VA?

For Data Science Engineer jobs in Alexandria, VA, the most frequently searched job titles are:

What job categories do people searching Data Science Engineer jobs in Alexandria, VA look for?

The top searched job categories for Data Science Engineer jobs in Alexandria, VA are:

What cities near Alexandria, VA are hiring for Data Science Engineer jobs?

Cities near Alexandria, VA with the most Data Science Engineer job openings:

Data Science Engineer jobs near you
Infographic showing various Data Science Engineer job openings in Alexandria, VA as of August 2026, with employment types broken down into 1% As Needed, 85% Full Time, 11% Part Time, and 3% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $138,837 per year, or $66.7 per hour.

Data Engineer / Data Scientist with Security Clearance

Indigo Industries, LLC

Arlington, VA • On-site

Other

Medical, Dental, Vision, Retirement, PTO

Re-posted 28 days ago

Key responsibilities

  • Design, develop, and maintain ontologies to structure complex mission data and ensure integration with Mission Engineering ontologies.

  • Develop, test, and support analytical and statistical models to assess system performance, gaps, and capabilities.

  • Translate mission requirements into logical data models and quantitative assessments, and synthesize data outputs into actionable insights for stakeholders.

Job description

Description:
• Position Title: Data Engineer / Data Scientist (Ontology and Data Science Engineer)
• Clearance Level: Secret
• Location: Arlington, VA, open to Hybrid/remote
• Reporting To: Lead for Digital Environments, APEX
• Travel: ~25% Role Overview:
The incumbent will play a critical role in structuring complex mission data and developing robust analytical models to support the assessment of Department of War (DoW) systems and capabilities. The primary focus of this role is supporting ontology development and ensuring seamless integration with Mission Engineering (ME) ontologies within the MEIA JCDE environment. The ideal candidate blends expertise in Model-Based Systems Engineering (MBSE), semantic data structuring, and statistical analysis to drive data-informed capability assessments. Responsibilities:
• Ontology Development & Integration: Design, develop, and maintain ontologies to structure complex data, ensuring alignment and integration with overarching Mission Engineering ontologies within the MEIA JCDE environment.
• Analytical Modeling: Develop, test, and support advanced analytical and statistical models to assess the performance, gaps, and effectiveness of current and proposed systems and capabilities.
• System Modeling: Utilize SysML to support MBSE efforts, mapping system architectures and behaviors to underlying data structures and ontologies.
• Data Translation: Act as a bridge between systems engineers and data architects, translating mission requirements into logical data models and quantitative assessments.
• Reporting & Visualization: Synthesize complex data science outputs and semantic queries into clear, actionable insights for mission stakeholders and decision-makers.Technical Liaison: Support the APEX by translating mission requirements into technical specifications for enterprise IT partners. Experience Requirements
Professional Experience:
• Professional Experience: Mid-level professional (5-8+ years) with data science, systems engineering, or ontology development experience.
• DoD Domain Context: Prior experience supporting DoD/DoW mission sets, processes, or data environments is a strong plus, though not a strict requirement.
• Data Science & Modeling Proficiency: Strong proficiency in Statistical Software, data science programming (e.g., Python, Pandas, Scikit-learn, R), and SysML for MBSE efforts.
• Semantic Web Expertise: Applied experience with semantic web technologies and ontology languages (e.g., OWL, RDF, SPARQL). Familiarity with graph databases (e.g., Neo4j, ArangoDB) and MBSE software (e.g., Cameo Systems Modeler) is highly desirable. Education & Certifications: • Education: Bachelor’s or Master's degree in Data Science, Systems Engineering, Computer Science, Mathematics, or a related technical field.
• Certifications: Relevant certifications in Data Science, MBSE (e.g., OCSMP), or Cloud infrastructure are preferred. Why work for Indigo?
At Indigo Industries, you'll do hands-on technical work on a mission that matters — and we back that up with benefits that support your life outside of it: -Paid time off — all federal holidays plus three weeks of accrued paid vacation.
-Employer-paid health insurance — Indigo currently covers the individual health insurance premium for eligible employees after a 30-day waiting period. Full plan details, including health coverage and available dental and vision options, are provided at hire.
-Retirement savings — SIMPLE IRA with up to 3% employer matching after a 30-day waiting period.

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