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Data Science Machine Learning Jobs in Maryland (NOW HIRING)

Agile Defense

Data Scientist

Fort George G Meade, MD

Preferred Skills and Experience 4+ years of experience in applied data science, machine learning engineering, or data pipeline development. Proficient in Python, SQL, and distributed data frameworks ...

Agile Defense

Data Scientist

Fort George G Meade, MD · On-site

Preferred Skills and Experience • 4+ years of experience in applied data science, machine learning engineering, or data pipeline development. • Proficient in Python, SQL, and distributed data ...

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All JobsData Science Machine Learning JobsData Science Machine Learning Jobs in Maryland

Data Science Machine Learning information

See Maryland salary details

$36.4K

$119.1K

$190.7K

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 Maryland is $119,123.00, according to ZipRecruiter salary data. Most workers in this role earn between $95,600.00 and $132,000.00 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 in Maryland are hiring for Data Science Machine Learning jobs? Cities in Maryland 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 Maryland 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 $119,123 per year, or $57.3 per hour.

Senior Software Engineer - Machine Learning / Data Science

Staffed4U

Laurel, MD • On-site

$220K - $240K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 2 days ago

Job description

Software Engineer - Level 3 (Machine Learning / Data Science)Location: Laurel, MD (Onsite)
Clearance: Active TS/SCI with Poly required
Citizenship: U.S. Citizenship required
Salary Range: $220,000-240,000Position Overview

We are seeking a highly experienced Software Engineer 3 (SWE-3) to support mission-critical government programs in Laurel, MD. The ideal candidate will possess extensive experience in software engineering, machine learning, and data analytics within secure government environments. This role requires hands-on development expertise, advanced analytical skills, and the ability to support agency compliance and operational standards.

Minimum Qualifications
  • Bachelor’s degree in Computer Science, Engineering, Mathematics, or related technical field plus 20 years of relevant experience
  • Active TS/SCI clearance with Polygraph
  • Ability to work on-site in Laurel, MD five days per week
Required Skills & Experience
  • Experience with Java, Scala, and Python
  • Experience with Lucene, JEXL, SQL, and JSON
  • Experience developing in Linux operating environments
  • Experience with Map/Reduce
  • Experience with GM Learn
  • Experience with Jupyter Notebooks
  • Experience with IntelliJ and/or Eclipse
  • Experience with Git/GitLab and/or Stash/Bitbucket
  • Experience with Jira and Confluence
  • Experience with Scikit-learn
  • Experience building and monitoring Machine Learning models
  • Experience with Random Forest algorithms and feature development
  • Understanding of Agency compliance standards, policies, and authorities
  • Experience working with Agency corporate systems
  • Experience creating, reviewing, and maintaining technical documentation
Desired Skills & Experience
  • Data Science background and analytical expertise
  • Experience with AWS cloud technologies
  • Experience implementing Machine Learning systems in production environments
  • Experience with Apache Spark
  • Experience performing Exploratory Data Analysis (EDA)
  • Experience with Agentic AI technologies
  • Experience working with Large Language Models (LLMs)
  • Experience with Machine Learning feature engineering and development
  • Familiarity with additional Machine Learning models and advanced analytical techniques
Preferred Attributes
  • Strong problem-solving and analytical capabilities
  • Ability to work independently and collaboratively within mission-focused teams
  • Excellent written and verbal communication skills
  • Experience supporting high-security government environments
Compensation & Benefits
  • Competitive salary based on experience and qualifications
  • Comprehensive benefits package
  • Opportunity to support impactful national security missions
  • 100% employer-paid Medical, Dental, and Vision coverage for employees and their families (CareFirst)
  • 401(k) with employer match
  • Generous Paid Time Off and paid holidays
  • Annual bonus opportunities
  • Employer-paid short-term and long-term disability insurance
  • Employer-paid life insurance (150% of salary, up to $200K)
  • Monthly stipend for cell phone and internet
  • Additional employee perks and recognition programs
 
We are an Equal Opportunity Employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity or expression, national origin, age, disability, veteran status, or any other protected status under applicable law.