1

Machine Learning Data Associate Jobs in Maryland

An Associate's degree plus 5 years of relevant experience may be considered for individuals with in ... Relevant experience must be in designing/implementing machine learning, data science, advanced ...

An Associate's degree plus 5 years of relevant experience may be considered for individuals with in ... Relevant experience must be in designing/implementing machine learning, data science, advanced ...

An Associate's degree plus 5 years of relevant experience may be considered for individuals with in ... Relevant experience must be in designing/implementing machine learning, data science, advanced ...

Data Scientist

Annapolis, MD · On-site

$119K - $285K/yr

Associates degree with 17 years of relevant experience * All Levels: * Bachelor'sDegree must be in Mathematics, Applied Mathematics Statistics, Applied Statistics, Machine learning, Data Science ...

Data Scientist 2

Annapolis, MD · On-site

$115K - $145K/yr

... Associates degree with 5 years of relevant experience * Bachelor's Degree must be in Mathematics, Applied Mathematics Statistics, Applied Statistics, Machine learning, Data Science, Operations ...

Data Scientist 4

Annapolis, MD · On-site

$212K - $267K/yr

Associate's degree with 17 years of experience may be considered for individuals with in-depth ... Relevant experience must be in designing/implementing machine learning, data science, advanced ...

Data Scientist 2

Annapolis Junction, MD · On-site

$115K - $145K/yr

... or an Associates degree with 5 years of relevant experience * Bachelor's Degree must be in Mathematics, Applied Mathematics Statistics, Applied Statistics, Machine learning, Data Science ...

Showing results 21-40

Machine Learning Data Associate information

See Maryland salary details

$9

$18

$29

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

As of Sep 12, 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:

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

Fort George G Meade, MD • On-site

Themis Insight
Business Management Consulting • 1 - 10 employees

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Re-posted 2 hours ago


Job description

Themis Insight solves difficult business, IT, and analytic problems by addressing the whole problem - not just the symptoms - using interdisciplinary approaches that are both practical and innovative. We provide fresh alternatives to ordinary, mainstream consulting firms through small, highly skilled, and hand-picked teams that can meet clients' needs in any industry. Our broad interdisciplinary understanding allows us to provide the right solution, even if it is from outside the industry or traditionally defined problem space. We bring Public and Private, Civilian and Military expertise to every case.
We are hiring a Data Scientist to work in the Fort Meade, MD vicinity. Position location is subject to change based on central MD client's needs.
Required: TS/SCI with a Polygraph
Employ some combination (2 or more) of the following skill areas:
  1. Foundations: Mathematical, Computational, Statistical
  2. Data Processing: Data management and curation, data description and visualization, workflow and reproducibility
  3. Modeling, Inference, and Prediction: Data modeling and assessment, domain-specific considerations

Devise strategies for extracting meaning and value from large datasets. Make and communicate principled conclusions from data using elements of mathematics, statistics, computer science, and application specific knowledge. Through 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 features and limitations inherent in NSA/CSS 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. Make informed recommendations regarding competing technical solutions by maintaining awareness of the constantly-shifting NSA/CSS collection, processing, storage and analytic capabilities and limitations.
Individual Capabilities/Experience Required:
  • A Bachelor's degree and 3 years of relevant experience. An Associate's degree plus 5 years of relevant experience may be considered for individuals with in-depth experience that is clearly related to the position.
  • Degree must be in Mathematics, Applied Mathematics, Statistics, Applied Statistics, Machine Learning, Data Science, Operations Research, or Computer Science. A degree in a related field (e.g., Computer Information Systems, Engineering), a degree in the physical/hard sciences (e.g. physics, chemistry, biology, social, and life) may be considered if it includes a concentration of coursework (typically 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 Algebra or other math courses designated as elementary or basic do not count.
  • Note: A 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 one high-level language (e.g. Python) and skill in at least one mid-level language (e.g. C)), data mining, advanced statistical analysis (e.g. statistical foundations of machine learning, statistical approaches to missing data, time series), advanced mathematical foundations (e.g. numerical methods, graph theory), artificial intelligence, workflow and reproducibility, data management and curation, data modeling and assessment (e.g. model selection, evaluation, and sensitivity analysis), experience as a data scientist working to support a single or multiple domain areas, and/or software engineering. Experience in more than three areas is strongly preferred.

Themis Insight has all the PERKS!
You are our most valuable resource - your ambition, your knowledge, your creativity. We offer an industry-leading set of benefits to supplement your normal salary compensation. Themis Insight has you covered with flexible ways to balance work and home life, full health benefit premium coverage, and generous contributions toward your retirement.
  • Competitive health, dental, and vision plans with 100% paid premiums.
  • 401k: We contribute 6% even if you don't!
  • Time Off: 11 standard holidays, and 25 days of PTO
  • Career Development: Get career counseling and individualized career development plans, including education and training.
  • Employee referral bonuses for successful hires

Themis Insight is an Equal Opportunity/Affirmative Action employer.
Themis Insight 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.