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Data Science Associate Jobs in Baltimore, MD (NOW HIRING)

Gormat

Data Scientist 4

Annapolis Junction, MD

... computer science, and applications-specific knowledge. * Ability to use analytic modeling ... Bachelor's Degree with 10 years of relevant experience, associate's degree with 12 years of ...

Gormat

Data Scientist 4

Annapolis Junction, MD · On-site

$174K - $189K/yr

... computer science, and applications-specific knowledge. * Ability to use analytic modeling ... Bachelor's Degree with 10 years of relevant experience, associate's degree with 12 years of ...

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Sentar

Data Scientist 3

Fort George G Meade, MD · On-site

This role involves leveraging your computer science expertise to develop and sustain analytics ... Bachelor's Degree with 10 years of relevant experience, Associates degree with 12 years of ...

Leidos

Data Scientist

Fort George G Meade, MD · On-site

$107K - $195K/yr

Associate's degree with 12 years of relevant experience may be considered. * Other degrees with strong coursework in advanced math, statistics, AI/ML, computer science, or data mining, or relevant ...

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All JobsData Science Associate JobsData Science Associate Jobs in Baltimore, MD

Data Science Associate information

See Baltimore, MD salary details

$57.1K

$67.6K

$128.2K

How much do data science associate jobs pay per year?

As of Jul 3, 2026, the average yearly pay for data science associate in Baltimore, MD is $67,606.00, according to ZipRecruiter salary data. Most workers in this role earn between $58,600.00 and $59,100.00 per year, depending on experience, location, and employer.

How does a Data Science Associate typically collaborate with other departments or teams within an organization?

Data Science Associates frequently work cross-functionally, partnering with teams such as engineering, product management, and business analytics to understand project requirements, share findings, and implement data-driven solutions. Collaboration often involves translating complex data results into actionable insights for non-technical stakeholders, ensuring alignment on project goals and deliverables. This role requires strong communication skills, as associates routinely participate in meetings, present analyses, and gather feedback to refine their models or analyses. Effective teamwork helps ensure that data science initiatives support broader business objectives.

Is 40 too late for data science?

Age is not a barrier to becoming a data science associate; many professionals transition into data science later in their careers. Success depends on acquiring relevant skills such as programming, statistics, and machine learning, often through online courses or certifications, regardless of age.

Is an Associates in data science worth it?

An associate's degree in data science can provide foundational skills in data analysis, programming, and statistics, which may help entry-level candidates qualify for junior data science roles. However, many employers prefer candidates with a bachelor's degree or higher, and practical experience or certifications in tools like Python, R, or SQL can enhance job prospects. The value depends on career goals and the specific requirements of potential employers.

What can I do with an associate's degree in data science?

A Data Science Associate with an associate's degree can work as a data analyst, supporting data collection, cleaning, and basic analysis using tools like Excel, SQL, and Python. They often assist in generating reports, visualizations, and insights under supervision, and may pursue certifications to enhance their skills for more advanced roles.

What are Data Science Associates?

Data Science Associates are early-career professionals who support data-driven projects by collecting, cleaning, analyzing, and interpreting large datasets. They typically work under the guidance of more experienced data scientists and help build predictive models, generate reports, and provide insights to inform business decisions. This role often requires proficiency in programming languages like Python or R, familiarity with statistical methods, and strong problem-solving skills. Data Science Associates play a crucial part in transforming raw data into actionable information for organizations.

What is the role of an associate data scientist?

An associate data scientist supports data analysis and modeling tasks by cleaning and processing data, developing algorithms, and creating visualizations. They often work under supervision to assist in building predictive models and may use tools like Python, R, or SQL to analyze data and generate insights.

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

To thrive as a Data Science Associate, you need strong analytical skills, a solid foundation in statistics and mathematics, and proficiency in programming languages like Python or R, often supported by a degree in data science, computer science, or a related field. Familiarity with machine learning frameworks, data visualization tools, and database systems such as SQL is typically required. Excellent problem-solving abilities, effective communication, and collaboration skills help you translate complex data insights into actionable business strategies. These skills are vital for extracting meaningful value from data and supporting data-driven decision-making within organizations.

What is the difference between Data Science Associate vs Data Analyst?

AspectData Science AssociateData Analyst
Required CredentialsBachelor's degree in Data Science, Statistics, or related field; some roles prefer certifications in data analysis or programmingBachelor's degree in Statistics, Mathematics, or related field; often no advanced certifications required
Work EnvironmentCollaborates with data scientists and engineers; involved in building models and algorithmsFocuses on data collection, cleaning, and reporting; supports decision-making
Employer & Industry UsageUsed in tech, finance, healthcare, and consulting firms for data-driven projectsCommon across various industries for business insights and reporting

The Data Science Associate role typically involves more technical work like building models and applying machine learning, whereas Data Analysts focus on interpreting data and creating reports. Both roles require strong analytical skills, but Data Science Associates often have a deeper understanding of programming and statistical modeling.

What are the most commonly searched types of Data Science jobs in Baltimore, MD? The most popular types of Data Science jobs in Baltimore, MD are:
What job categories do people searching Data Science Associate jobs in Baltimore, MD look for? The top searched job categories for Data Science Associate jobs in Baltimore, MD are:
What cities near Baltimore, MD are hiring for Data Science Associate jobs? Cities near Baltimore, MD with the most Data Science Associate job openings:
Data Science Associate jobs near you
Infographic showing various Data Science Associate job openings in Baltimore, MD as of June 2026, with employment types broken down into 71% Full Time, and 29% Part Time. Highlights an 86% In-person, and 14% Remote job distribution, with an average salary of $67,606 per year, or $32.5 per hour.
Data Scientist Level 3

Data Scientist Level 3

IntelliGenesis LLC®

Annapolis Junction, MD • On-site

Full-time

Posted 7 days ago

Job description

Job Summary:
IntelliGenesis LLC® is a company focused on mission operations in the cybersecurity domain, and they are seeking a Data Scientist Level 3. The role involves employing a variety of skills to extract meaning from large datasets, communicate insights, and develop technical requirements based on practical mission needs.
Responsibilities:
• Employ some combination (2 or more) of the following skill areas: 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)
• 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 other 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 customer data holdings
• Translate practical mission needs and analytic questions related to large datasets into technical requirements and, conversely, assist other 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 constantly shifting collection, processing, storage and analytic capabilities and limitations
Qualifications:
Required:
• US Citizens Only
• Active TS/SCI Clearance and Polygraph required
• Information Assurance Certification may be required
• Minimum of eight (8) years of relevant experience and a Master's degree; ten (10) years of relevant experience and a Bachelor’s degree or 12 years of relevant experience and an Associate’s degree required.
• Degree must be in Mathematics, Applied Mathematics, Statistics, Applied Statistics, Machine Learning, Data Science, Operations Research, or Computer Science
• 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 two of more of the following: Designing/implementing machine learning, Data science, Advanced analytical algorithms, Programming (skill in at least one 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, Software engineering
Company:
IntelliGenesis delivers AI, cyber, data, and workforce capabilities for national security and high-consequence environments. Founded in 2007, the company is headquartered in Columbia, USA, with a team of 51-200 employees. The company is currently Growth Stage.

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