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Data Science Assistant Jobs in Georgia (NOW HIRING)

Data Science & Analysis Travel Required: Up to 10% Clearance Required: Ability to Obtain Public ... Support cloud-based data environments and services in AWS and Azure. * Assist with the ...

Data Engineer

Atlanta, GA · On-site

$53K - $88K/yr

Data Science & Analysis Travel Required: Up to 10% Clearance Required: Ability to Obtain Public ... Support cloud-based data environments and services in AWS and Azure. * Assist with the ...

Ensure data accuracy and integrity by implementing quality control processes * Assist in presenting ... Bachelor's degree in a relevant field (e.g., Data Science, Computer Science, Statistics) * Proven ...

Ensure data accuracy and integrity by implementing quality control processes * Assist in presenting ... Qualifications * Bachelor's degree in a relevant field (e.g., Data Science, Computer Science ...

Senior Data Scientist I

Alpharetta, GA · On-site

$95K - $158K/yr

... to assist them in evaluating and predicting risk and enhancing operational efficiency. Our ... Requirements * Experience leading complex data science or attribute development projects ...

Data Eng Sr

Augusta, GA · On-site

$88K - $149K/yr

The Geospatial Data Engineer will be expected to assist in efforts such as, but not limited to ... OR BA/BS degree in Data Science, Data Analytics, Informatics, Statistics, or related field AND 10 ...

Public Health Data Engineer

Atlanta, GA · On-site

$110K - $132K/yr

Data Science & Analysis Travel Required: Up to 10% Clearance Required: Ability to Obtain Public ... Support cloud-based data environments and services in AWS and Azure. * Assist with the ...

Public Health Data Engineer

Atlanta, GA · On-site

$70K - $116K/yr

Data Science & Analysis Travel Required: Up to 10% Clearance Required: Ability to Obtain Public ... Support cloud-based data environments and services in AWS and Azure. * Assist with the ...

Showing results 21-40

Data Science Assistant information

What is a data science assistant?

Data Science Assistants are professionals who support data scientists and analytics teams by handling tasks such as data collection, data cleaning, preparing datasets, conducting preliminary analyses, and creating visualizations. They often work with large datasets, assist in maintaining data integrity, and help automate routine processes. Their role allows data scientists to focus on more complex modeling and analytical work, making the overall workflow more efficient. Data Science Assistants typically have a foundational understanding of statistics, programming (such as Python or R), and data management tools.

What are the key skills and qualifications needed to thrive as a data science assistant?

To thrive as a Data Science Assistant, you need a solid understanding of statistics, data analysis, and programming (often with a background in mathematics, computer science, or a related field). Familiarity with tools like Python or R, data visualization software, and experience with databases or spreadsheet systems are typically required. Attention to detail, strong problem-solving abilities, and effective communication set outstanding candidates apart. These skills are crucial for supporting data-driven decision-making and ensuring accurate, actionable insights for organizations.

How does a data science assistant typically collaborate with data scientists and other team members on projects?

As a Data Science Assistant, you will frequently support data scientists by preparing datasets, conducting preliminary data analysis, and creating visualizations. You will often work closely with analysts, engineers, and subject matter experts to gather requirements and ensure data is cleaned and formatted appropriately. Collaboration is a key part of the role, as you may participate in team meetings, share findings, and help with documentation to keep projects running smoothly. This supportive environment provides an excellent opportunity to learn from experienced professionals and gain exposure to the full data science workflow.

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

AspectData Science AssistantData Analyst
Required CredentialsBachelor's in Data Science, Statistics, or related fieldBachelor's in Statistics, Mathematics, or related field
Work EnvironmentTech companies, research labs, data-driven departmentsBusiness, finance, marketing, healthcare sectors
Employer & Industry UsageUsed in data science teams for supporting models and analysisUsed across industries for interpreting data and generating reports

While both roles involve working with data, a Data Science Assistant typically supports data science projects, focusing on data preparation and model testing. A Data Analyst primarily interprets data to generate insights and reports. The roles overlap in skills and work environments but differ in their core responsibilities and focus areas.

What are the most commonly searched types of Data Science jobs in Georgia?

The most popular types of Data Science jobs in Georgia are:

What are popular job titles related to Data Science Assistant jobs in Georgia?

For Data Science Assistant jobs in Georgia, the most frequently searched job titles are:

What job categories do people searching Data Science Assistant jobs in Georgia look for?

The top searched job categories for Data Science Assistant jobs in Georgia are:

What cities in Georgia are hiring for Data Science Assistant jobs?

Cities in Georgia with the most Data Science Assistant job openings:

Infographic showing various Data Science Assistant job openings in Georgia as of August 2026, with employment types broken down into 5% Internship, 76% Full Time, 10% Part Time, 2% Temporary, and 7% Contract. Highlights an 95% In-person, and 5% Remote job distribution.

Data Scientist - multiple levels - CLEARANCE and POLYGRAPH REQUIRED

Constellation Technologies, Inc

Augusta, GA • On-site

Full-time

Re-posted just now


Job description

Job Summary:
Constellation Technologies, Inc is seeking a Data Scientist with a focus on Big Data and Artificial Intelligence/Machine Learning. The role involves developing strategies for data analysis, communicating findings, and translating mission needs into technical requirements.
Responsibilities:
• 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 to Agency 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 Agency collection, processing, storage and analytic capabilities and limitations.
Qualifications:
Required:
• Must be a US Citizen
• Must have TS/SCI clearance w/ active polygraph
• This position is open to multiple levels of years of experience; two (02) years within the last five (05) years must be directly related to the job you are applying for:
• Level 04 requires a minimum seventeen (17) years of experience w/ Degree
• Level 03 requires a minimum twelve (12) years of experience w/ Degree
• Level 02 requires a minimum five (05) years of experience w/ Degree
• Degree 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, astronomy), or other science disciplines with a substantial computational component (i.e., behavioral, 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 intended to meet a basic college level requirement, or upper-level math courses designated as elementary or basic do not count.
• 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.
• Employ some combination (2 or more) of the following 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 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 to Agency 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 Agency collection, processing, storage and analytic capabilities and limitations.
Preferred:
• Fully Cleared polygraph is preferred
• Knowledge of working with Big Data, dataflows, Machine Learning/Artificial Intelligence familiarity.
• Analytics in GME, Jupyter notebooks, and Spark.
Company:
Constellation Technologies, Inc. Founded in 2008, the company is headquartered in Columbia, USA, with a team of 51-200 employees. The company is currently Growth Stage.