ZipRecruiter

Log In

1

Data Science Machine Learning Jobs in Silver Spring, MD

Parsons

Machine Learning / Data Scientist

Washington, DC · On-site

$88K - $154K/yr

The Machine Learning / Data Scientist is a hands-on practitioner with strong capabilities in model ... Bachelor's degree in Data Science, Statistics, Computer Science, Mathematics, or a closely related ...

Cmu

Data Scientist

Arlington, VA

Requirements: * BS in data science, machine learning, computer science, statistics, or related highly-quantitative discipline with eight (8) years of experience or equivalent combination of training ...

Cmu

Associate Data Scientist

Arlington, VA

$67K - $68K/yr

Requirements: * BS in data science, machine learning, computer science, statistics, or related highly-quantitative discipline with three (3) years of experience or equivalent combination of training ...

Fannie Mae

Data Science Advisor

Washington, DC

You will apply expertise in data science, machine learning, AI, large-scale data processing, computational programming, and practical problem solving, while clearly explaining technical solutions to ...

SOSi

Data Scientist III

Washington, DC

This role is responsible for applying data science, machine learning, and data engineering techniques to enhance enterprise security monitoring, detection, threat hunting, user and entity behavior ...

SOSi

Data Scientist III

Washington, DC · On-site

This role is responsible for applying data science, machine learning, and data engineering techniques to enhance enterprise security monitoring, detection, threat hunting, user and entity behavior ...

SOSi

Data Scientist III

Washington, DC · On-site

This role is responsible for applying data science, machine learning, and data engineering techniques to enhance enterprise security monitoring, detection, threat hunting, user and entity behavior ...

KDA Consulting Inc

Data Scientist

Chantilly, VA · On-site

Bachelor's degree in Data Science, Computer Science, Mathematics, Statistics, or a related field (or equivalent experience) Strong experience in data science, machine learning, and statistical ...

Fanniemae

Audit Data Science Advisor

Reston, VA · On-site

You will apply deep expertise in data science, machine learning, AI techniques, large-scale data processing, computational programming, and practical problem solving, with the ability to clearly ...

KDA Consulting Inc

Data Scientist

Herndon, VA · On-site

Bachelor's degree in Data Science, Computer Science, Mathematics, Statistics, or a related field (or equivalent experience) Strong experience in data science, machine learning, and statistical ...

KDA Consulting Inc

Data Scientist

Mclean, VA · On-site

Bachelor's degree in Data Science, Computer Science, Mathematics, Statistics, or a related field (or equivalent experience) Strong experience in data science, machine learning, and statistical ...

Fanniemae

Audit Data Science Advisor

Washington, DC · On-site

You will apply deep expertise in data science, machine learning, AI techniques, large-scale data processing, computational programming, and practical problem solving, with the ability to clearly ...

KDA Consulting Inc

Data Scientist

Chantilly, VA · On-site

Bachelor's degree in Data Science, Computer Science, Mathematics, Statistics, or a related field (or equivalent experience) Strong experience in data science, machine learning, and statistical ...

next page

Showing results 1-20

All JobsData Science Machine Learning JobsData Science Machine Learning Jobs in Silver Spring, MD

Data Science Machine Learning information

See Silver Spring, MD salary details

$38.6K

$126.5K

$202.5K

How much do data science machine learning jobs pay per year?

As of Jun 29, 2026, the average yearly pay for data science machine learning in Silver Spring, MD is $126,496.00, according to ZipRecruiter salary data. Most workers in this role earn between $101,500.00 and $140,200.00 per year, depending on experience, location, and employer.

Which has more salary, CS or AI?

Data Science and Machine Learning roles in AI generally have higher salaries than traditional computer science positions due to specialized skills in deep learning, neural networks, and advanced algorithms. AI roles often require expertise in programming languages like Python and frameworks such as TensorFlow, which are highly valued in the job market. Salaries vary by experience, location, and industry, but AI-focused positions tend to offer higher compensation on average.

What are the key skills and qualifications needed to thrive as a Data Science Machine Learning professional, and why are they important?

To thrive as a Data Science Machine Learning professional, you need a strong background in statistics, programming (usually Python or R), and a solid understanding of machine learning algorithms, often supported by a degree in computer science, mathematics, or a related field. Familiarity with tools like TensorFlow, scikit-learn, SQL databases, and cloud platforms, as well as certifications such as AWS Certified Machine Learning, are typically valuable. Critical thinking, problem-solving, and effective communication are vital soft skills for interpreting data and collaborating with stakeholders. These skills enable professionals to develop robust models, extract actionable insights, and drive data-driven decision-making in organizations.

What engineers make $500,000?

Senior data science and machine learning engineers with extensive experience, advanced skills in programming, statistical analysis, and deep learning, and often working in high-demand industries or at large tech companies can earn $500,000 or more annually. Compensation typically includes base salary, bonuses, and stock options, especially at executive or specialized levels.

What are some common challenges faced when deploying machine learning models as a Data Science Machine Learning professional?

A frequent challenge in this role is bridging the gap between building accurate models in a controlled environment and deploying them effectively in production systems. Issues such as data drift, model performance degradation, and integration with existing IT infrastructure often arise. Collaboration with engineering and IT teams is crucial to ensure models are scalable, maintainable, and secure. Regular monitoring and updating of deployed models are also essential responsibilities to sustain their value to the business.

What is the difference between Data Science Machine Learning vs Data Analyst?

AspectData Science Machine LearningData Analyst
Required SkillsProgramming (Python, R), statistics, machine learning algorithmsData visualization, SQL, basic statistics
Work EnvironmentDeveloping models, coding, experimenting with algorithmsData reporting, dashboard creation, data cleaning
Industry UsageTech, finance, healthcare, where predictive models are neededBusiness intelligence, marketing, operations

Data Science Machine Learning professionals focus on building predictive models and algorithms using programming and advanced statistics, often working on complex projects. Data Analysts primarily interpret data through visualization and reporting to support business decisions. While both roles require data skills, Data Science Machine Learning involves more technical programming and modeling, whereas Data Analysts focus on data interpretation and presentation.

Do data scientists work with machine learning?

Data scientists often work with machine learning as a core part of their role, developing models to analyze data and make predictions. They use tools like Python, R, and libraries such as scikit-learn or TensorFlow to build and deploy machine learning algorithms. Knowledge of statistics, programming, and data manipulation is essential for this work.

What is data science machine learning?

Data science machine learning refers to the use of algorithms and statistical models to analyze and draw insights from complex data sets. In this field, professionals use machine learning techniques to build predictive models, automate decision-making processes, and uncover patterns in data. Machine learning is a core component of data science, enabling systems to improve their performance over time without being explicitly programmed. Data scientists with machine learning expertise are in high demand across industries like healthcare, finance, and technology.

Which 3 jobs will survive AI?

Data science and machine learning roles are expected to persist as they require complex problem-solving, domain expertise, and creativity that AI tools currently cannot fully replicate. Jobs involving strategic decision-making, ethical considerations, and interpersonal skills, such as data analysts, AI ethics specialists, and AI system trainers, are also likely to remain in demand. Continuous learning and proficiency with AI tools will be essential for these roles to adapt and thrive.
What cities near Silver Spring, MD are hiring for Data Science Machine Learning jobs? Cities near Silver Spring, MD with the most Data Science Machine Learning job openings:
Data Science Machine Learning jobs near you
Infographic showing various Data Science Machine Learning job openings in Silver Spring, MD as of June 2026, with employment types broken down into 62% Full Time, 36% Part Time, and 2% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $126,496 per year, or $60.8 per hour.
Machine Learning / Data Scientist

Machine Learning / Data Scientist

Parsons

Washington, DC • On-site

$88K - $154K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 24 days ago

Key responsibilities

  • Design and implement machine learning and advanced analytics solutions that address operational, programmatic, or strategic questions.

  • Develop, train, and validate models using appropriate techniques and tools, and evaluate model performance to improve accuracy and interpretability.

  • Collaborate with stakeholders to define analytical problems, identify relevant data, and translate business needs into modeling requirements.

Parsons rating

7.9

Company rating: 7.9 out of 10

Based on 44 frontline employees who took The Breakroom Quiz

159th of 356 rated engineering

Job description

In a world of possibilities, pursue one with endless opportunities. Imagine Next!At Parsons, you can imagine a career where you thrive, work with exceptional people, and be yourself. Guided by our leadership vision of valuing people, embracing agility, and fostering growth, we cultivate an innovative culture that empowers you to achieve your full potential. Unleash your talent and redefine what's possible.

Job Description:

We have a career opportunity for a Machine Learning / Data Scientist to develop advanced analytical models and experiments that enhance decision-making, improve forecasting, and uncover insights across mission and support activities. This role would be based in Washington, DC. Would be required to be on-site

This role will support the enablement of machine learning capabilities within our analytics environment, working closely with data analysts, engineers, and program stakeholders.

The Machine Learning / Data Scientist is a hands-on practitioner with strong capabilities in model development, data preparation, and analytical storytelling. This role requires the ability to frame complex problems, select appropriate modeling approaches, implement and validate models, and communicate results in accessible terms to non-technical audiences.

Key Responsibilities:

  • Design and implement machine learning and advanced analytics solutions that address operational, programmatic, or strategic questions.
  • Collaborate with stakeholders to define analytical problems, identify relevant data, and translate business needs into modeling requirements.
  • Prepare and engineer features from multiple data sources, ensuring data quality and suitability for modeling.
  • Develop, train, and validate models (e.g., classification, regression, clustering, forecasting) using appropriate techniques and tools.
  • Evaluate model performance, perform error analysis, and refine approaches to improve accuracy, robustness, and interpretability.
  • Integrate model outputs into dashboards, applications, or automated workflows, in coordination with analytics and development teams.
  • Document modeling approaches, assumptions, and results, and communicate findings through clear narratives and visualizations.
  • Support experimentation and pilot projects that explore new analytical techniques and tools.
  • Contribute to the development of standards and practices for responsible and sustainable use of advanced analytics.

Typical Assignments:

  • Building predictive or prescriptive models that support prioritization of projects, resource allocation, or risk assessment.
  • Conducting exploratory data analysis to identify patterns, anomalies, and opportunities for improved performance.
  • Developing prototypes of ML-enabled features that can be integrated into existing dashboards or applications.
  • Supporting performance management by providing advanced analyses of trends and drivers underlying key metrics.
  • Collaborating with data management staff to ensure datasets are suitable for modeling and reproducible analysis.
  • Preparing technical and non-technical presentations that summarize modeling methods, findings, and implications.

Education and Experience:

  • Bachelor's degree in Data Science, Statistics, Computer Science, Mathematics, or a closely related field; a master's degree is preferred but not required, or equivalent work experience.
  • 5+ years of experience in data science, machine learning, or advanced analytics roles.
  • Demonstrated experience developing, validating, and deploying machine learning models using tools such as Python, R, or equivalent.
  • Strong background in statistics, model evaluation, and experimental design.
  • Experience with data preparation, feature engineering, and working with complex, multi-source datasets.
  • Familiarity with integrating model outputs into BI tools or applications (e.g., via APIs, embedded analytics) is preferred.
  • Experience working within mission-oriented or public sector environments (e.g., DHS, DoD) is a plus.

Security Clearance Requirement:

NoneThis position is part of our Critical Infrastructure team.For more than 80 years, our experts have designed and delivered the critical infrastructure that connects and protects communities around the world. We work in collaborative teams, both within the company and with our partners and customers, to plan, design, build, and modernize infrastructure. We take special pride in projects and solutions that improve communities as well as people's quality of life by promoting economic growth, enhancing mobility, and increasing sustainability and resiliency. Powered by our people, we provide the imagination necessary to support our customers' visions-and to help them see what's next!Salary Range: $88,400.00 - $154,700.00We value our employees and want our employees to take care of their overall wellbeing, which is why we offer best-in-class benefits such as medical, dental, vision, paid time off, Employee Stock Ownership Plan (ESOP), 401(k), life insurance, flexible work schedules, and holidays to fit your busy lifestyle!Parsons is an equal opportunity employer, and all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability, veteran status or any other protected status.We truly invest and care about our employee's wellbeing and provide endless growth opportunities as the sky is the limit, so aim for the stars! Imagine next and join the Parsons quest-APPLY TODAY!

Parsons is aware of fraudulent recruitment practices. To learn more about recruitment fraud and how to report it, please refer tohttps://www.parsons.com/fraudulent-recruitment/.

What Parsons employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom

Apply