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Data Scientist Software Engineer Jobs (NOW HIRING)

Bachelor's degree in computer science, Software Engineering, or related field. Required: * TS/SCI with Full Scope Polygraph * BS in a quantitative field (mathematics, data science, statistics) * At ...

You will work closely with senior data scientists, software engineers, and Product Management to translate business requirements into actionable insights and ML capabilities. This role offers the ...

You will work closely with senior data scientists, software engineers, and Product Management to translate business requirements into actionable insights and ML capabilities. This role offers the ...

... software developers, operators, project managers, and clients to prepare data for predictive ... data science, machine learning (ML), or statistics. • Demonstrated high level of initiative ...

Data Scientist

Chantilly, VA · On-site +1

$200K - $240K/yr

Collaborating with other data scientists, software developers, operators, project managers, and clients to prepare data for predictive modeling. * Documents internal process improvements to optimize ...

... Software Engineering, or related field. • TS/SCI with Full Scope Polygraph • BS in a ... data science, statistics) • At least 3 years of demonstrated experience directly relevant to ...

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Data Scientist Software Engineer information

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$46K

$165K

$243.5K

How much do data scientist software engineer jobs pay per year?

As of Aug 21, 2026, the average yearly pay for data scientist software engineer in the United States is $165,018.00, according to ZipRecruiter salary data. Most workers in this role earn between $133,500.00 and $170,000.00 per year, depending on experience, location, and employer.

What is a data scientist software engineer?

A Data Scientist Software Engineer is a professional who combines expertise in software engineering and data science. They build scalable systems and tools for processing, analyzing, and interpreting large datasets. Their responsibilities often include designing algorithms, developing machine learning models, and deploying data-driven applications. This hybrid role requires strong programming skills, a solid understanding of statistical analysis, and the ability to translate data insights into actionable solutions within software products.

What does a data scientist software engineer do?

Data Scientist Software Engineers often split their time between developing robust data pipelines and building scalable software solutions. A typical day may involve analyzing datasets, creating or refining machine learning models, and then integrating these models into production software environments. They collaborate closely with data analysts, software engineers, and product managers to ensure that data-driven features are both accurate and maintainable. Balancing these responsibilities requires strong time management and communication skills to align technical deliverables with business objectives.

What are the key skills and qualifications needed to thrive as a data scientist software engineer?

To thrive as a Data Scientist Software Engineer, you need strong programming skills (especially in Python, R, or Java), a solid foundation in math and statistics, and a relevant degree (such as computer science, statistics, or engineering). Proficiency with data analysis libraries (like Pandas, NumPy, and scikit-learn), machine learning frameworks (such as TensorFlow or PyTorch), and experience with cloud platforms and version control systems are highly valued. Critical thinking, problem-solving, and effective communication are essential soft skills for collaborating with teams and translating data insights into software solutions. These skills are crucial for building robust, data-driven applications and ensuring impactful business outcomes.

What is the difference between Data Scientist Software Engineer vs Data Engineer?

AspectData Scientist Software EngineerData Engineer
CredentialsBachelor's or Master's in CS, Data Science, or related fields; often includes certifications in machine learning or data analysisBachelor's or Master's in CS, Software Engineering, or related fields; certifications in cloud platforms or data tools are common
Work EnvironmentCollaborates with data scientists and software developers; focuses on building data-driven applications and modelsBuilds and maintains data pipelines, databases, and infrastructure; works closely with data teams and software engineers
Industry UsageUsed across tech, finance, healthcare, and e-commerce sectors for analytics and product developmentPrimarily in organizations managing large-scale data storage, processing, and infrastructure

Data Scientist Software Engineers combine skills in software development and data science to create data-driven applications, whereas Data Engineers focus on building the infrastructure for data storage and processing. Both roles are essential in data-centric organizations but serve different functions within the data ecosystem.

Can a data scientist software engineer work as a data scientist?

A data scientist software engineer can often transition to a data scientist role if they have relevant skills such as statistical analysis, machine learning, and data visualization. Both roles require strong programming skills, typically in Python or R, and familiarity with data tools and frameworks. However, specific job requirements may vary depending on the organization and the complexity of data analysis tasks involved.
More about Data Scientist Software Engineer jobs
Infographic showing various Data Scientist Software Engineer job openings in the United States as of August 2026, with employment types broken down into 1% As Needed, 85% Full Time, 11% Part Time, and 3% Contract. Highlights an 85% Physical, 4% Hybrid, and 11% Remote job distribution, with an average salary of $165,018 per year, or $79.3 per hour.

Data Scientist / AI Engineer

Ironclad Defense Works

Norfolk, VA • On-site

Full-time

Medical, Dental, Retirement, PTO

Posted 18 days ago


Job description

Data Scientist / AI Engineer
Location: Norfolk, Virginia
Employment Type: Full-time, On-site
Security Clearance: Active NATO or U.S. National SECRET clearance required
Citizenship: Must be a citizen of a NATO member nation
The Role
Ironclad is seeking an experienced Data Scientist / AI Engineer to support the development and implementation of advanced data science, artificial intelligence, and large language model capabilities within the NATO enterprise.
This position requires a technically versatile professional who can bridge data engineering, software development, machine learning, and operational mission requirements. The selected candidate will design scalable data architectures, build and optimize data pipelines, develop API-based infrastructure, and support the secure deployment of AI and machine learning solutions in cloud-based and hybrid environments.
The role requires strong hands-on experience with generative AI, large language models (LLMs), distributed systems, microservices, containerized applications, and modern software engineering practices. The successful candidate must also be able to translate complex operational challenges into practical technical solutions for military and civilian stakeholders.
Key Responsibilities
  • Develop and implement scalable data science and AI capabilities supporting NATO initiatives.
  • Design, build, and maintain data pipelines for structured and unstructured data.
  • Prepare, cleanse, transform, and optimize data for LLM training, fine-tuning, inference, and analytics.
  • Develop API-based infrastructure that integrates LLMs and machine learning models with operational systems.
  • Design and support microservices and containerized AI/ML applications.
  • Build distributed data storage and processing solutions using cloud-based or hybrid architectures.
  • Develop real-time data processing and streaming capabilities for operational decision support.
  • Automate data engineering processes and improve the scalability, efficiency, and reliability of AI infrastructure.
  • Implement monitoring, logging, traceability, and performance-optimization tools for data pipelines and APIs.
  • Support the secure deployment of AI and LLM solutions in Microsoft Azure, AWS, or comparable environments.
  • Develop tools that improve data accessibility for data scientists, analysts, engineers, and operational users.
  • Collaborate with data scientists, software engineers, system architects, and other technical stakeholders.
  • Support federated learning, cross-domain data sharing, and secure collaboration across NATO nations.
  • Develop proofs of concept for LLM-based and advanced analytics applications.
  • Evaluate operational requirements and recommend appropriate AI, software, and data-engineering solutions.
  • Create dashboards, reports, and visual analytics for senior and non-technical stakeholders.
  • Provide technical briefings, mentoring, and training in AI engineering, data science, API development, and digital literacy.
  • Research emerging developments in generative AI, distributed computing, data architecture, and software engineering.
  • Promote responsible, secure, and ethical AI practices throughout solution development and deployment.
Required Qualifications
  • Bachelor’s degree or higher from a nationally recognized university in data science, data analytics, artificial intelligence, mathematics, physics, computer science, software engineering, or a closely related discipline.
  • At least four years of professional experience as a Data Scientist, Machine Learning Engineer, Data Engineer, Software Engineer, or in a closely related role.
  • Demonstrated experience developing operational AI or machine learning solutions.
  • Experience with distributed systems and cloud-based or hybrid architectures.
  • Experience designing API-based infrastructure and microservices architectures.
  • Hands-on experience developing and deploying containerized applications using technologies such as Docker or Kubernetes.
  • Demonstrated experience with generative AI and large language models.
  • Experience preprocessing data and supporting the fine-tuning and deployment of LLMs in secure, scalable environments.
  • Experience with machine learning frameworks such as TensorFlow, PyTorch, scikit-learn, or comparable technologies.
  • Strong programming experience with Python, Java, Scala, or similar languages.
  • Experience with version control, CI/CD pipelines, automated testing, and modern software engineering practices.
  • Experience building and optimizing ETL processes, data pipelines, and real-time streaming solutions.
  • Familiarity with Apache Airflow, Kafka, Spark, or comparable data-engineering technologies.
  • Experience architecting or maintaining data lakes, data warehouses, distributed storage systems, or NoSQL solutions.
  • Knowledge of platforms such as Delta Lake, Snowflake, Hadoop, or comparable technologies.
  • Experience applying AI to operational decision support and the analysis of unstructured data, including text or imagery.
  • Strong understanding of data security, privacy, sovereignty, and responsible AI practices.
  • Experience developing dashboards, visual reports, and analytics using Tableau, Microsoft Power BI, Kibana, or comparable tools.
  • Ability to translate operational problems into practical AI and machine learning solutions.
  • Demonstrated success working with multidisciplinary technical teams.
  • Strong written and verbal communication skills.
  • Ability to explain technical concepts to non-technical stakeholders and senior leaders.
  • Ability to mentor or train personnel in AI engineering, data science, or software development concepts.
Preferred Qualifications
  • Familiarity with NATO processes, organizational structures, operational culture, and decision-making procedures.
  • Experience supporting military, defense, government, or international organizations.
  • Experience developing AI or data-engineering solutions using open-source frameworks and publicly available datasets.
  • Familiarity with military staff workflows and operational planning processes.
  • Experience with federated learning and privacy-preserving collaboration across multiple organizations or nations.
  • Experience supporting cross-domain data sharing and API-driven interoperability.
  • Familiarity with agile project-management methods and tools such as JIRA, Trello, or Microsoft Loop.
  • Experience briefing senior leaders and presenting actionable, data-driven recommendations.
  • Knowledge of ethical AI principles, including bias mitigation, responsible data handling, transparency, and secure deployment.
Why Join Ironclad
Ironclad supports complex defense and international missions by providing experienced professionals who combine technical expertise with an understanding of operational requirements. This position offers the opportunity to contribute directly to secure, scalable, and mission-focused AI capabilities while working alongside military, civilian, and technical stakeholders across the NATO enterprise.
Clearance
This position requires an active NATO or National SECRET (or higher) security clearance. Applicants who do not possess the clearance specified above cannot be considered at this time. 
Compensation
Compensation for this position ranges from $115,000 - $130,000 annually. Final salary will be based on factors such as experience, education, skills, qualifications, contract requirements, and overall affordability. 
Eligible full-time employees may also receive a comprehensive benefits package, including medical and dental insurance, retirement benefits, paid leave, and professional development opportunities. 
How to Apply
Email your resume to jobs@idw.inc with the subject line: Data Scientist / AI Engineer
- (Your Name) Application" or respond to this job posting via the included web application.
Ironclad Defense Works is an Equal Opportunity Employer.
 

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