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Data Scientist Machine Learning Jobs in Baltimore, MD

Agile Defense

Data Scientist

Fort George G Meade, MD

Data Scientist / Engineer Clearance: Top Secret with ability to obtain SCI and CI Poly Location: Ft ... This role is part of a multidisciplinary team integrating advanced analytics, machine learning, and ...

Index Analytics

Senior Data Scientist

Baltimore, MD · On-site +1

$155K - $194K/yr

This role emphasizes end-to-end development of machine learning and AI systems, including ... The Senior Data Scientist serves as a technical leader on AI initiatives, helping guide solution ...

Tror AI for everyone

Data Scientist

Baltimore, MD · On-site

Data Scientist Location: Baltimore, MD (Onsite) Hiring Type: Contract Job Summary: We are seeking a ... Key Responsibilities: • Design, develop, and deploy machine learning and NLP models for text ...

Gormat

Data Scientist 2

Annapolis Junction, MD · On-site

$99K - $114K/yr

You will also provide advanced discovery support using machine learning, analytical prototyping ... The Level 2 Data Scientist shall possess the following capabilities: * Foundations: (Mathematical ...

Elder Research

Data Scientist

Fort George G Meade, MD · On-site

... Scientists to support the U.S. Intelligence Community. The role involves developing advanced ... Responsibilities : • Develop and implement machine learning, data mining, statistical, and graph ...

Gormat

Data Scientist 2

Annapolis Junction, MD · On-site

$99K - $114K/yr

You will also provide advanced discovery support using machine learning, analytical prototyping ... The Level 2 Data Scientist shall possess the following capabilities: * Foundations: (Mathematical ...

Gormat

Data Scientist 2

Annapolis Junction, MD · On-site

You will also provide advanced discovery support using machine learning, analytical prototyping ... The Level 2 Data Scientist shall possess the following capabilities: * Foundations: (Mathematical ...

Gormat

Data Scientist 3

Annapolis Junction, MD · On-site

$132K - $147K/yr

Bachelor's Degree must be in Mathematics, Applied Mathematics Statistics, Applied Statistics, Machine learning, Data Science, Operations Research, or Computer Science or a degree in a related field ...

Gormat

Data Scientist 3

Annapolis Junction, MD · On-site

$132K - $147K/yr

Bachelor's Degree must be in Mathematics, Applied Mathematics Statistics, Applied Statistics, Machine learning, Data Science, Operations Research, or Computer Science or a degree in a related field ...

Gormat

Data Scientist 3

Annapolis Junction, MD

Bachelor'sDegree must be in Mathematics, Applied Mathematics Statistics, Applied Statistics, Machine learning, Data Science, Operations Research, or Computer Science or a degree in a related field ...

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All JobsData Scientist Machine Learning JobsData Scientist Machine Learning Jobs in Baltimore, MD

Data Scientist Machine Learning information

See Baltimore, MD salary details

$37.3K

$122K

$195.2K

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

As of Jul 18, 2026, the average yearly pay for data scientist machine learning in Baltimore, MD is $121,952.00, according to ZipRecruiter salary data. Most workers in this role earn between $97,900.00 and $135,100.00 per year, depending on experience, location, and employer.

What is a Data Scientist Machine Learning job?

A Data Scientist specializing in Machine Learning (ML) uses statistical methods, algorithms, and computational power to analyze data and create predictive models. They work with large datasets to identify patterns, train machine learning models, and improve decision-making processes. Responsibilities often include data cleaning, feature engineering, model selection, and performance evaluation. They may collaborate with engineers and business teams to deploy models in real-world applications. Strong skills in programming (Python, R), ML frameworks (TensorFlow, Scikit-learn), and data visualization are essential.

What are the key skills and qualifications needed to thrive in the Data Scientist Machine Learning position, and why are they important?

To excel as a Data Scientist Machine Learning, you need a strong proficiency in statistics, programming (typically Python or R), and a solid understanding of machine learning algorithms, usually backed by a degree in computer science, mathematics, or a related field. Familiarity with tools such as TensorFlow, scikit-learn, SQL databases, and cloud platforms, as well as certifications in data science or machine learning, is commonly expected. Analytical thinking, problem-solving skills, and effective communication are vital soft skills in this profession. These qualifications combine to drive impactful insights and enable the successful development and deployment of machine learning models in business environments.

Is 40 too late for data science?

Data scientists can enter the field at any age, including 40 or older, 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 machine learning tools. Age is less important than demonstrated expertise and the ability to adapt to evolving technologies.

Will MLE be replaced by AI?

Machine Learning Engineers (MLEs) design, develop, and deploy AI models, and while AI automation tools can assist with certain tasks, MLEs are essential for creating and maintaining complex systems. AI is a tool that enhances their work but does not replace the need for skilled professionals who understand data, algorithms, and system integration.

Which 5 jobs will survive AI?

Data Scientist Machine Learning roles are likely to persist as they require complex problem-solving, domain expertise, and the ability to interpret and communicate insights from data. Jobs that involve creativity, emotional intelligence, and strategic decision-making, such as healthcare professionals, educators, and skilled trades, are also expected to remain resilient despite AI advancements.

What are the typical day-to-day responsibilities of a Data Scientist Machine Learning?

On a typical day, a Data Scientist specializing in Machine Learning might gather and preprocess data, design and implement machine learning models, and evaluate their performance to solve real-world problems. They often collaborate with data engineers, software developers, and business stakeholders to translate business objectives into technical solutions and integrate models into existing systems. Other responsibilities can include visualizing data insights, conducting experiments to tune algorithms, and staying current with new developments in the field. The work is highly collaborative and iterative, requiring clear communication with various teams to ensure project goals are met efficiently.

Do data scientists do machine learning?

Yes, data scientists often use machine learning techniques to analyze data, build predictive models, and extract insights. Proficiency in programming languages like Python or R and understanding of algorithms are essential skills for applying machine learning in their work.
What are the most commonly searched types of Data Scientist Machine Learning jobs in Baltimore, MD? The most popular types of Data Scientist Machine Learning jobs in Baltimore, MD are:
What are popular job titles related to Data Scientist Machine Learning jobs in Baltimore, MD? For Data Scientist Machine Learning jobs in Baltimore, MD, the most frequently searched job titles are:
What job categories do people searching Data Scientist Machine Learning jobs in Baltimore, MD look for? The top searched job categories for Data Scientist Machine Learning jobs in Baltimore, MD are:
What cities near Baltimore, MD are hiring for Data Scientist Machine Learning jobs? Cities near Baltimore, MD with the most Data Scientist Machine Learning job openings:
Data Scientist Machine Learning jobs near you
Infographic showing various Data Scientist Machine Learning job openings in Baltimore, MD as of July 2026, with employment types broken down into 1% As Needed, 83% Full Time, 13% Part Time, and 3% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $121,952 per year, or $58.6 per hour.
Data Scientist

Data Scientist

Agile Defense

Fort George G Meade, MD

Other

Medical, Life, Retirement, PTO

Re-posted 6 days ago

Job description

About Agile Defense
 
At Agile Defense we know that action defines the outcome and new challenges require new solutions. That's why we always look to the future and embrace change with an unmovable spirit and the courage to build for what comes next.
 
Our vision is to bring adaptive innovation to support our nation's most important missions through the seamless integration of advanced technologies, elite minds, and unparalleled agility-leveraging a foundation of speed, flexibility, and ingenuity to strengthen and protect our nation's vital interests.

Requisition #: 1424
Title: Data Scientist / Engineer
Clearance: Top Secret with ability to obtain SCI and CI Poly
Location: Ft. Meade, MD
 
Role Summary
 
Agile Defense is seeking a Data Scientist / Engineer to support the design, development, and operational deployment of scalable, AI-enabled data solutions within the Department of Defense's CDAO ADA IR program. This role is part of a multidisciplinary team integrating advanced analytics, machine learning, and engineering practices into mission-critical environments at CYBERCOM.
 
You will help shape and deploy data pipelines, pre-processing workflows, feature engineering strategies, and machine learning services within secure, containerized environments. The ideal candidate brings a hybrid of statistical modeling fluency and hands-on software engineering expertise. You will collaborate closely with product managers, full-stack developers, platform engineers, and mission stakeholders to transform raw data into meaningful insights and decision-support tools.
This role requires strong technical communication skills, a collaborative mindset, and experience working in agile environments that value reproducibility, testing, and continuous delivery. Familiarity with cloud-based data platforms such as Databricks, Palantir, or AWS-native data services is highly preferred.
 
 
Key Objectives
 
Objective 1: Design and Maintain Scalable Data Science Services
Plan, develop, and maintain reusable services for data ingestion, transformation, and feature engineering that support AI/ML workflows.
Implement core data science capabilities, such as entity resolution, classification, clustering, or prediction, within containerized environments that adhere to CI/CD, version control, and testing standards.
Collaborate with DevSecOps engineers to integrate services into secure production environments using tools like Databricks, Docker, and Terraform.
Ensure services meet performance, reliability, and security requirements consistent with DoD enterprise and cloud-native architecture.
Objective 2: Build and Operationalize AI/ML Solutions
Develop and deploy standalone or embedded ML models for tasks such as decision support, automation, anomaly detection, and pattern recognition.
Select and implement appropriate modeling techniques using Python, Spark, or cloud-native ML frameworks (e.g., SageMaker, MLflow).
Maintain reproducibility and interpretability of model outputs to meet mission transparency and audit requirements.
Package model inference services with well-documented APIs for integration into end-user applications and operational dashboards.
Objective 3: Perform Exploratory Data Analysis and Communicate Insights
Conduct exploratory data analysis (EDA) to identify trends, gaps, and opportunities within structured and unstructured datasets.
Develop data visualizations and interpretive summaries that support stakeholder understanding and product team decision-making.
Translate analytical findings into actionable recommendations using a mix of visual, narrative, and quantitative communication strategies.
Contribute to the team's shared library of analysis templates, reusable queries, and analytic workflows to accelerate future delivery.
Objective 4: Collaborate Across Teams to Deliver Mission Impact
Engage with product managers and mission users to define data and model requirements aligned with operational goals.
Work closely with engineers to ensure data science components align with technical constraints and deployment patterns.
Participate in agile sprint planning, retrospectives, and demos, sharing progress and adjusting priorities based on feedback.
Maintain strong documentation practices that enable handoff, reproducibility, and technical accountability.
 
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 (e.g., Spark, Databricks, PySpark).
Experience developing ML models from training to deployment using industry-standard tools and libraries (e.g., scikit-learn, TensorFlow, XGBoost, MLflow).
Familiarity with MLOps, API development, and secure cloud-based environments (e.g., AWS, Azure, Palantir Foundry).
Strong understanding of data validation, model testing, and performance evaluation techniques.
Experience with data visualization and storytelling using tools such as Tableau, Plotly, or Matplotlib.
Excellent technical communication skills, with the ability to explain complex concepts to non-technical audiences.
$125,000 - $145,000 a year
In addition, Agile Defense invests in its employees beyond just compensation.  Agile's benefits offerings include, dependent upon position, Health Insurance, Life Insurance, Paid Time Off, Holiday Pay, short-term and long-term Disability, Retirement and Learning and Development opportunities as well as other optional benefit elections.
Our Core Values
 
Employees of Agile Defense are our number one priority, and the importance we place on our culture here is fundamental. Our culture is alive and evolving, but it always stays true to its roots. Here, you are valued as a family member, and we believe that we can accomplish great things together. Agile Defense has been highly successful in the past few years due to our employees and the culture we create together. 
 
What makes us Agile? We call it the 6Hs, the values that define our culture and guide everything we do. Together, these values infuse vibrancy, integrity, and a tireless work ethic into advancing the most important national security and critical civilian missions. It's how we show up every day. It's who we are.
 
  • Happy - Be Infectious. Happiness multiplies and creates a positive and connected environment where motivation and satisfaction have an outsized effect on everything we do.
  • Helpful - Be Supportive. Being helpful is the foundation of teamwork, resulting in a supportive atmosphere where collaboration flourishes, and collective success is celebrated.
  • Honest - Be Trustworthy. Honesty serves as our compass, ensuring transparent communication and ethical conduct, essential to who we are and the complex domains we support.
  • Humble - Be Grounded. Success is not achieved alone, humility ensures a culture of mutual respect, encouraging open communication, and a willingness to learn from one another and take on any task.
  • Hungry - Be Eager. Our hunger for excellence drives an insatiable appetite for innovation and continuous improvement, propelling us forward in the face of new and unprecedented challenges.
  • Hustle - Be Driven. Hustle is reflected in our relentless work ethic, where we are each committed to going above and beyond to advance the mission and achieve success.
 
Equal Opportunity Employer/Protected Veterans/Individuals with Disabilities
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
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