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Machine Learning Data Associate Jobs in Maryland

iNovex Information Systems

Data Scientist 2

Annapolis, MD · On-site

$122K - $168K/yr

You will also provide advanced discovery support using machine learning, analytical prototyping ... Bachelor's Degree with 3 years of relevant experience, associate's degree with 5 years of ...

iNovex Information Systems

Data Scientist 3

Annapolis, MD · On-site

$157K - $215K/yr

Associates degree with 12 years of relevant experience. * Bachelor'sDegree must be in Mathematics, Applied Mathematics Statistics, Applied Statistics, Machine learning, Data Science, Operations ...

iNovex Information Systems

Data Scientist 2

Annapolis, MD · On-site

$122K - $168K/yr

You will also provide advanced discovery support using machine learning, analytical prototyping ... Bachelor's Degree with 3 years of relevant experience, associate's degree with 5 years of ...

ManTech

Data Scientist

Fort George G Meade, MD · Remote

$128K - $214K/yr

Develop and implement machine learning, data mining, statistical, and graph-based algorithms to analyze large and complex datasets. * Prototype and evaluate multiple algorithms, selecting the final ...

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Machine Learning Data Associate information

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How much do machine learning data associate jobs pay per hour?

As of Sep 13, 2026, the average hourly pay for machine learning data associate in Maryland is $18.19, according to ZipRecruiter salary data. Most workers in this role earn between $14.95 and $19.38 per hour, depending on experience, location, and employer.

What is a machine learning data associate?

Machine Learning Data Associates are professionals who support the development of machine learning models by preparing, labeling, and validating data sets. Their work ensures that data used for training algorithms is accurate, consistent, and properly annotated. They may also assist with data cleaning, quality checks, and sometimes basic data analysis tasks. This role is crucial in industries where high-quality labeled data is essential for building effective AI systems.

What are the key skills and qualifications needed to thrive as a machine learning data associate?

To thrive as a Machine Learning Data Associate, you need strong analytical skills, attention to detail, and a basic understanding of data annotation and labeling processes, often supported by a degree in computer science or a related field. Familiarity with data management tools, annotation platforms, and sometimes scripting languages like Python is typically required. Strong communication, collaboration, and problem-solving abilities help you work efficiently with data science teams and ensure high-quality outcomes. These skills and qualities are crucial for producing accurate datasets that directly impact the effectiveness of machine learning models.

How does a machine learning data associate typically collaborate with data scientists and engineers within a project team?

As a Machine Learning Data Associate, you play a vital role in supporting data scientists and engineers by annotating, cleaning, and organizing large datasets to ensure high data quality. You'll frequently communicate with team members to clarify labeling guidelines, provide feedback on data inconsistencies, and report any edge cases encountered during annotation. This collaboration ensures that the datasets used for training machine learning models are accurate and comprehensive, directly impacting the success of the project. Expect regular team meetings and ongoing feedback loops to maintain alignment with evolving project requirements.

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

AspectMachine Learning Data AssociateData Analyst
Required SkillsData cleaning, labeling, basic programming, understanding of ML workflowsData interpretation, visualization, statistical analysis
Work EnvironmentTech companies, AI startups, research labsBusiness, finance, marketing, healthcare sectors
Common CertificationsData Science certifications, Python, SQLExcel, Tableau, SQL certifications

The main difference is that Machine Learning Data Associates focus on preparing and labeling data specifically for machine learning models, while Data Analysts interpret data to generate insights for business decisions. Both roles require strong data skills and often overlap, but their primary objectives and work environments differ.

How do I become a machine learning data associate?

To become a machine learning data associate, candidates typically need a high school diploma or equivalent, with some roles preferring a bachelor's degree in computer science, data science, or related fields. Relevant skills include data annotation, understanding of machine learning concepts, and proficiency with tools like Excel, SQL, or data labeling platforms. Gaining experience through internships or certifications can improve job prospects in this field.

Is a Machine Learning Data Associate a good job?

A Machine Learning Data Associate role involves preparing and managing data for machine learning models, often requiring skills in data cleaning, annotation, and familiarity with tools like Python or SQL. It can be a good entry-level position for those interested in AI and data science, offering opportunities to develop technical skills and gain industry experience. Compensation and job satisfaction vary depending on the employer and location, but it generally provides a solid foundation for a career in machine learning or data analysis.

What cities in Maryland are hiring for Machine Learning Data Associate jobs?

Cities in Maryland with the most Machine Learning Data Associate job openings:

Machine Learning Data Associate jobs near you
Infographic showing various Machine Learning Data Associate job openings in Maryland as of August 2026, with employment types broken down into 1% As Needed, 83% Full Time, 13% Part Time, and 3% Contract. Highlights an 85% Physical, 4% Hybrid, and 11% Remote job distribution, with an average salary of $37,826 per year, or $18.2 per hour.

Data Scientist 2 with Security Clearance

Baltimore, MD • On-site

RealmOne
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Job description

Are you VIGILANT about your career? RealmOne definitely is! RealmOne was built on the principle that people matter first and foremost. We believe in providing a strong work/life balance by investing in our employees and encouraging professional and personal growth. We do this by offering exceptional benefits, flexible schedules, and the tools necessary to achieve success through paid training, mentoring, and the opportunity to work alongside top-notch industry professionals. Join us on this journey as we execute this mission-critical contract providing high-end analytics and data science services within the REALM of cybersecurity. Your effort and expertise are crucial to the success and execution of this impactful mission. This opportunity supports a team of Data Scientists, Cryptologic Computer Scientists, Cryptanalytic Computer Scientists, Cryptologic Cyber Planners, Intrusion Analysts, Protocol Analysts, Signals Analysts and Reverse Engineers, responsible for improving, protecting, and defending our Nation's Security. Job Description: * We are seeking a Data Scientist with a primary focus of using AI/ML experience to impact and assess large datasets. This includes data modeling, computational mathematics, qualitative and quantitative techniques, data visualizations, and AI/ML model development and deployment. You will conduct advanced statistical and predictive modeling and large scale data processing using Spark and/or cloud data platforms. You will also provide advanced discovery support using machine learning, analytical prototyping, scripting, automation, data visualization, statistical analysis, and TechSIGINT tools. You will need to be adaptable to new tools and technologies as needed.The Level 2 Data Scientist shall possess the following capabilities: * Foundations: (Mathematical, Computational, Statistical).
* Data Processing: (Data management and curation, data description and visualization, workflow and reproducibility).
* Modeling, Inference, and Prediction: (Data modeling and assessment, domain-specific considerations).
* Ability to make and communicate principal conclusions from data using elements of mathematics, statistics, computer science, and applications-specific knowledge. * Ability to use analytic modeling, statistical analysis, programming, and/or another appropriate scientific method, develop and implement qualitative and quantitative methods for characterizing, exploring, and assessing large datasets in various states of organization, cleanliness, and structure that account for the unique feature and limitations inherent in Customer data holdings. * Translate practical mission needs and analytic questions related to large datasets into technical requirements and, conversely, assist others with drawing appropriate conclusions from the analysis of such data. * Effectively communicate complex technical information to non-technical audiences. Qualifications: * Bachelor's Degree with 3 years of relevant experience, associate's degree with 5 years of experience may be considered for individuals with in-depth experience that is clearly related to the position. * 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 (Computer Information Systems, Engineering), a degree in the physical/hard sciences (e.g. physics, chemistry, biology, astronomy), or other science disciplines with a substantial computational component (i.e. behavioral, social, or life) may be considered if it included a concentration of coursework (5 or more courses) in advanced Mathematics (typically 300 level or higher, such as linear algebra, probability and statistics, machine learning) and/or computer science (e.g. algorithms, programming, , data structures, data mining, artificial intelligence). College-level requirement, or upper-level math courses designated as elementary or basic do not count. * Broader range of degrees will be considered if accompanied by a Certificate in Data Science from an accredited college/university. * Relevant experience must be in designing/implementing machine learning, data science, advanced analytical algorithms, programming (skill in at least on high level language (e.g. Python), statistical analysis (e.g. variability, sampling error, inference, hypothesis testing, EDA, application of linear models), data management (e.g. data cleaning and transformation), data mining, data modeling and assessment, artificial intelligence, and/or software engineering. Position requires active Security Clearance with appropriate Polygraph

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