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Data Science Software Engineer Jobs in Washington

Data Engineering Lead

Arlington, VA · On-site

$131K - $158K/yr

... Science, Software Engineering • Active TS/SCI clearance Company : Accenture Federal Services is a leading US federal services company and subsidiary of Accenture. Founded in 1989, the company is ...

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 ...

Software Engineer

Annapolis Junction, MD · On-site

$100.96 - $115.38/hr

Job Title Software Engineer Overview EverWatch is a government solutions company providing advanced ... Experience with Neo4j, Cypher, APOC, and Graph Data Science (GDS) libraries * Experience with ...

You Have: * 2+ years of experience within data engineering, software engineering, data science, or data analytics * 2+ years of experience developing and maintaining scalable data stores that supply ...

Data Engineer

Mclean, VA

$115K - $139K/yr

Bachelor's degree in computer science, Software Engineering, or related field. * 5+ years of experience in data engineering or a related field * Strong proficiency in SQL and experience with ...

Data Engineer

Arlington, VA · On-site

$62K - $141K/yr

You Have: * 2+ years of experience within data engineering, software engineering, data science, or data analytics * 2+ years of experience developing and maintaining scalable data stores that supply ...

Data Engineer

Arlington, VA · On-site

$62K - $141K/yr

You Have: * 2+ years of experience within data engineering, software engineering, data science, or data analytics * 2+ years of experience developing and maintaining scalable data stores that supply ...

Data Engineer

Arlington, VA · On-site +1

$62K - $141K/yr

You Have: * 2+ years of experience within data engineering, software engineering, data science, or data analytics * 2+ years of experience developing and maintaining scalable data stores that supply ...

Data Engineer

Herndon, VA · On-site

$117K - $141K/yr

Bachelor's degree in computer science, Software Engineering, or related field. * 5+ years of experience in data engineering or a related field * Strong proficiency in SQL and experience with ...

Data Engineer

Chantilly, VA · On-site

$118K - $142K/yr

Bachelor's degree in computer science, Software Engineering, or related field. * 5+ years of experience in data engineering or a related field * Strong proficiency in SQL and experience with ...

Data Engineer

Rockville, MD · On-site

$116K - $140K/yr

... and data science applications to research centers and healthcare organizations nationally and ... With experts in biomedical science, software engineering, and program management, we focus on ...

Data Engineer

Rockville, MD

$116K - $140K/yr

... and data science applications to research centers and healthcare organizations nationally and ... With experts in biomedical science, software engineering, and program management, we focus on ...

Data Engineer

Rockville, MD

$116K - $140K/yr

... and data science applications to research centers and healthcare organizations nationally and ... With experts in biomedical science, software engineering, and program management, we focus on ...

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Showing results 1-20

Data Science Software Engineer information

See Washington salary details

$50.4K

$146.9K

$201K

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

As of Jul 22, 2026, the average yearly pay for data science software engineer in Washington is $146,916.00, according to ZipRecruiter salary data. Most workers in this role earn between $129,700.00 and $155,700.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Data Science Software Engineer, and why are they important?

To thrive as a Data Science Software Engineer, you need strong proficiency in programming (especially Python or R), a solid understanding of statistics and algorithms, and typically a degree in computer science, data science, or a related field. Familiarity with machine learning frameworks (such as TensorFlow or scikit-learn), data processing tools (like Spark or Hadoop), and cloud platforms (AWS, GCP, or Azure) is essential, as are relevant certifications. Excellent problem-solving abilities, communication skills, and the ability to work collaboratively with cross-functional teams set top performers apart. These competencies are vital for efficiently developing scalable data-driven solutions that drive business insights and innovation.

How does a Data Science Software Engineer typically collaborate with data scientists and other stakeholders on projects?

Data Science Software Engineers play a vital role in bridging the gap between data science and software engineering teams. They work closely with data scientists to translate prototypes and models into scalable, production-ready code, and often collaborate with product managers, analysts, and infrastructure engineers to ensure seamless integration. Regular communication and code reviews are essential, as is an iterative development process to address feedback and ensure solutions meet both technical and business requirements. This cross-functional collaboration helps deliver robust data-driven applications that align with organizational goals.

Which is the hardest field in it?

For a Data Science Software Engineer, the most challenging fields often involve complex machine learning algorithms, large-scale data processing, and advanced statistical analysis. Staying current with rapidly evolving tools like Python, R, and cloud platforms also requires continuous learning and adaptation. These areas demand strong problem-solving skills and deep technical knowledge.

What is a Data Science Software Engineer?

A Data Science Software Engineer is a professional who combines software engineering skills with data science expertise to build scalable data-driven systems and applications. They design, develop, and optimize software that supports data pipelines, machine learning models, and analytics platforms. Their work bridges the gap between data scientists, who focus on statistical analysis and modeling, and traditional software engineers, who focus on building robust and efficient software systems. Data Science Software Engineers ensure that data solutions are production-ready, scalable, and maintainable.

Can a software engineer work as a data scientist?

A software engineer can transition to a data scientist role by developing skills in statistics, machine learning, and data analysis, often using tools like Python, R, and SQL. While the roles have different focuses, software engineers' programming expertise can be a strong foundation for data science work, especially with additional training or experience in data modeling and analytics.

Is 40 too late for data science?

Data science software engineers can enter the field 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 tools like Python or R. Age is not a barrier if you develop the necessary technical expertise and stay current with industry trends.

What engineers make $500,000?

Senior data science software engineers with extensive experience, advanced skills in machine learning, and proficiency in tools like Python, R, and cloud platforms can reach salaries of $500,000 or more, especially in high-cost-of-living areas or within large tech companies. Compensation often includes base salary, bonuses, and stock options, reflecting their expertise and impact on business outcomes.

What is the difference between Data Science Software Engineer vs Data Analyst?

AspectData Science Software EngineerData Analyst
Required SkillsProgramming, software development, machine learningData visualization, statistical analysis, reporting
Work EnvironmentSoftware development teams, engineering projectsBusiness units, reporting teams
Common ToolsPython, Java, SQL, ML frameworksExcel, Tableau, SQL, R
Industry UsageTech, finance, healthcare, startupsMarketing, finance, retail, research

While both roles analyze data, Data Science Software Engineers focus on developing software solutions and machine learning models, requiring strong programming skills. Data Analysts primarily interpret data through visualization and statistical methods to support business decisions. The roles often overlap but serve different functions within organizations.

What are popular job titles related to Data Science Software Engineer jobs in Washington? For Data Science Software Engineer jobs in Washington, the most frequently searched job titles are:
What job categories do people searching Data Science Software Engineer jobs in Washington look for? The top searched job categories for Data Science Software Engineer jobs in Washington are:
What cities in Washington are hiring for Data Science Software Engineer jobs? Cities in Washington with the most Data Science Software Engineer job openings:
Infographic showing various Data Science Software Engineer job openings in Washington as of July 2026, with employment types broken down into 1% As Needed, 82% Full Time, 12% Part Time, 1% Temporary, and 4% Contract. Highlights an 88% Physical, 3% Hybrid, and 9% Remote job distribution, with an average salary of $146,916 per year, or $70.6 per hour.
NLM Software Engineer I

Full-time

Medical, Dental, Life, Retirement, PTO

Posted 25 days ago


Job description

Software Engineer I


Lexical Intelligence provides software and services related to processing large-scale biomedical information sources. Our Natural Language Processing (NLP) and analytics software is used by policy and decision makers to evaluate and prioritize current and emerging areas of research.


We are looking for a Software Engineer I to work within the National Library of Medicine (NLM), Lister Hill National Center for Biomedical Communications (LHNCBC), Bethesda, MD. The Software Engineer I will have experience in software development, application design and testing, and web-based interface development. The Software Engineer I will have a firm understanding of modern programming languages, software development lifecycle (SDLC) methodologies, and secure coding practices. The Software Engineer I shall be able to work well within a team of multidisciplinary researchers, DevOps engineers, data scientists, and biomedical informatics professionals. The selected applicant will be subject to a pre-employment background and reference check.


Required Qualifications

  • 2+ years of relevant software development or engineering experience
  • Bachelor's degree or other degree(s) in Computer Science, Software Engineering, Information Technology, or related fields
  • Proficiency in one or more programming languages including Python, Java, JavaScript, C++, R, or SQL
  • Familiarity with software development lifecycle (SDLC) methodologies, including design, implementation, testing, deployment, and maintenance
  • Experience with or exposure to web-based application development, including responsive and RESTful design principles
  • Basic understanding of secure coding best practices as directed by US-CERT standards and OWASP guidelines
  • Familiarity with version control systems such as Git, GitHub, or GitLab
  • Strong written and oral communication skills, with the ability to communicate technical concepts clearly to diverse audiences
  • Must be authorized to work in the United States and able to obtain a Public Trust background investigation clearance

Preferred Qualifications

  • Experience with additional programming languages or environments including Matlab, SAS, ETL, MySQL, MongoDB, Jupyter Notebooks, or shell scripting
  • Familiarity with AI, Machine Learning (ML), Deep Learning (DL), Natural Language Processing (NLP), or Image Processing (IP) concepts and tools
  • Exposure to cloud computing platforms such as Google Cloud (GC), Amazon Web Services (AWS), or Microsoft Azure, including IaaS, PaaS, and SaaS configurations
  • Experience with containerization and orchestration tools such as Docker or Kubernetes
  • Familiarity with CI/CD pipelines and automated testing environments
  • Experience with Section 508 accessibility compliance standards and web content accessibility guidelines (WCAG 2.0)
  • Familiarity with Agile and Scrum project management frameworks
  • Experience developing applications for Linux, Windows, MacOS, Android, or mobile/handheld environments
  • Exposure to emerging AI tools such as ChatGPT or GitHub Copilot
  • Familiarity with federal IT security frameworks including FISMA and NIST standards

Responsibilities

  • Participate in all phases of the software development lifecycle, including inception, analysis, design, implementation, testing, deployment, and maintenance of software applications and tools
  • Perform software analysis, design, development, testing, and maintenance primarily in Linux environments, with work also spanning Windows, MacOS, Android, web-based, and mobile platforms
  • Develop applications using programming languages and environments including C++, Python, Java, JavaScript, R, Matlab, SAS, ETL, SQL, MySQL, MongoDB, and Jupyter Notebooks, with openness to adopting additional languages as the technical landscape evolves
  • Contribute to the design and development of web-based and user interfaces based on user needs analyses, design prototyping, and evaluation using graphic design, data visualization, and user-centered design techniques
  • Ensure all developed interfaces meet Section 508 compliance requirements and relevant design standards such as Responsive and RESTful design
  • Collaborate with NLM's Research Computing and Data Science Support teams, including the Office of Computer and Communications Systems (OCCS) and LHNCBC's Scientific Computing Branch (SCB), to ensure systems comply with security policies
  • Ensure developed system architectures are secure, extensible, and able to integrate with existing internal or external systems
  • Ensure that all developed software is thoroughly documented for internal and external users and future maintenance purposes
  • Leverage commercial cloud computing services (GC, AWS, Azure) to make tools publicly available, working across IaaS, PaaS, SaaS, and CI/CD configurations
  • Utilize managed cloud services including container orchestration, object and document stores, SQL databases, message brokers, and search engines
  • Conduct software testing and quality control employing automated testing environments and configuration management best practices
  • Provide support for projects and initiatives across disciplines including clinical research, biology, computational biology, data and computer science, AI, ML, DL, NLP, and program management
  • Assist in the design and implementation of AI and other technology projects for the Center for Clinical Observational Investigations
  • Document technical project requirements and track development timelines, identifying and coordinating internal and external dependencies
  • Assist in generating status updates for management, keeping stakeholders informed of progress, changes to project plans, and potential issues using appropriate communication channels
  • Participate as a team member in resource analysis, design, estimation, development, testing, and maintenance activities
  • Utilize Agile and Scrum project management frameworks to ensure project deliverables are met within defined timelines, including use of tools such as JIRA and Confluence Wiki
  • Follow secure coding best practices as directed by US-CERT standards and OWASP guidelines to limit system software vulnerability exploits
  • Ensure IT applications are designed and developed to run in standard user context without requiring elevated administrative privileges
  • Ensure all developed software is fully functional and operates correctly on systems configured in accordance with government policy and federal configuration standards, including testing with all relevant updates and patches prior to installation in the HHS environment
  • Comply with all HHS/NIH information security policies, including completing mandatory annual security awareness, privacy, and records management training
  • Adhere to HHS Rules of Behavior and the NLM Policy on Health-Related Data About Individuals, including signing required non-disclosure agreements prior to performing work
  • Report all suspected or confirmed information security incidents or breaches to the NIH Incident Response Team within one (1) hour of discovery
  • Protect sensitive information including PII, PHI, and proprietary data in accordance with FIPS 140-2/140-3 validated encryption standards


Salary and Benefits

We offer a competitive salary and a generous benefits package, including at no cost: full health and dental for you and your dependents, retirement and HSA accounts, short- and long-term disability insurance, life and accident insurance, paid time off, and 11 federal holidays.


Location

Bethesda, MD (NIH Campus, Building 38A)


Equal Employment Opportunity Policy

Lexical Intelligence, LLC, provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws.


This policy applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation and training.


Lexical Intelligence, LLC | 2001 Veirs Mill Rd #546 | Rockville, MD 20851