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Data Science Jobs in North Augusta, SC (NOW HIRING)

Prescient Edge

Senior Data Engineer

Augusta, GA · On-site

$100 - $120/hr

MA or MS in Data Science, Data Analytics, Informatics, Statistics, or related field AND 5 years CURRENT Intelligence Analysis experience; * BA or BS in Data Science, Data Analytics, Informatics ...

BAE Systems

Data Eng Sr

Augusta, GA · On-site

$106K - $127K/yr

OR BA/BS degree in Data Science, Data Analytics, Informatics, Statistics, or related field AND 10 years CURRENT Intelligence Analysis experience; OR HS diploma/GED AND Specialized Training with 15 ...

E&M Technologies, Inc.

Senior Data Engineer

Augusta, GA · On-site

$98K - $133K/yr

Master's degree in Data Science, Data Analytics, Informatics, Statistics, or related field plus 5 years of current Intelligence Analysis experience; OR Bachelor's degree in Data Science, Data ...

New

E&M Technologies, Inc.

Senior Data Engineer

Augusta, GA

$98K - $133K/yr

Master's degree in Data Science, Data Analytics, Informatics, Statistics, or related field plus 5 years of current Intelligence Analysis experience; OR Bachelor's degree in Data Science, Data ...

New

Prescient Edge

Senior Data Engineer

Augusta, GA · On-site

$98K - $133K/yr

MA or MS in Data Science, Data Analytics, Informatics, Statistics, or related field AND 5 years CURRENT Intelligence Analysis experience; * BA or BS in Data Science, Data Analytics, Informatics ...

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All JobsData Science JobsData Science Jobs in North Augusta, SC

Data Science information

See North Augusta, SC salary details

$35.2K

$115.4K

$184.7K

How much do data science jobs pay per year?

As of Sep 6, 2026, the average yearly pay for data science in North Augusta, SC is $115,357.00, according to ZipRecruiter salary data. Most workers in this role earn between $92,600.00 and $127,800.00 per year, depending on experience, location, and employer.

What is data science?

Data science is an interdisciplinary field that uses scientific methods, algorithms, and systems to extract insights and knowledge from structured and unstructured data. It combines skills from statistics, computer science, and domain expertise to analyze and interpret complex data sets. Data scientists work with large amounts of data to identify patterns, make predictions, and help organizations make data-driven decisions.

What does a data scientist do?

As a Data Scientist, you are qualified to work in such diverse fields as research and development, politics, advertising and marketing, technology, healthcare, government, and higher education as well as multiple others. In general, your duties and responsibilities will be to compile and analyze relevant statistics and turn those numbers into algorithms that reveal insights that can be used by other researchers in their areas of study. Data Science can reveal things like consumer buying habits or the likelihood of success for a course of action. Other duties might vary, depending on your unique field of specialty. Related areas in which a Data Scientist might wish to focus include work as a Data Analyst, Machine Learning Engineer, and Project Manager.

What are the key skills and qualifications needed to thrive as a data scientist, and why are they important?

To thrive as a Data Scientist, you need a strong background in statistics, programming (often Python or R), and data analysis, usually supported by a degree in a quantitative field. Familiarity with machine learning libraries (like scikit-learn or TensorFlow), big data tools (such as Hadoop or Spark), and data visualization platforms is typically required. Critical thinking, problem-solving, and effective communication are vital soft skills for translating complex data insights into actionable business strategies. These skills and qualities are essential for extracting value from data, driving informed decisions, and effectively collaborating with multidisciplinary teams.

What are some common challenges faced by data scientists when working with real-world datasets?

Data scientists often encounter challenges such as missing or inconsistent data, unstructured formats, and noisy information in real-world datasets. Cleaning and preprocessing data to ensure its quality can be time-consuming but is critical for building accurate models. Additionally, data scientists may work closely with domain experts and other team members to better understand the data's context and ensure their analyses align with business objectives. Overcoming these challenges requires strong problem-solving skills and effective collaboration within cross-functional teams.

What is the difference between Data Science vs Data Analyst?

AspectData ScienceData Analyst
Required skillsStatistics, programming (Python, R), machine learningData visualization, SQL, basic statistics
Work environmentDeveloping models, predictive analytics, researchReporting, data cleaning, descriptive analysis
Tools usedPython, R, Jupyter, TensorFlowExcel, SQL, Tableau, Power BI
Industry usageTech, finance, healthcare, e-commerceRetail, marketing, finance, healthcare

Data Science and Data Analyst roles often overlap but differ mainly in scope. Data Scientists focus on building predictive models and advanced analytics, requiring programming and machine learning skills. Data Analysts primarily handle data cleaning, reporting, and visualization. Both roles are essential in data-driven industries, but Data Science is more technical and research-oriented, while Data Analysis emphasizes interpreting data for business insights.

Is a data scientist in high demand?

Data scientists are in high demand across many industries due to the increasing reliance on data-driven decision making. The role requires skills in programming, statistics, and machine learning, and job growth is expected to continue as organizations expand their data capabilities.

What jobs can a data scientist do?

A data scientist can work in roles such as data analyst, machine learning engineer, data engineer, or business intelligence analyst. These roles involve analyzing large datasets, developing predictive models, and using tools like Python, R, and SQL to support decision-making across various industries.
More about Data Science jobs

What are the most commonly searched types of Data Science jobs in North Augusta, SC?

The most popular types of Data Science jobs in North Augusta, SC are:

What are popular job titles related to Data Science jobs in North Augusta, SC?

For Data Science jobs in North Augusta, SC, the most frequently searched job titles are:

What cities near North Augusta, SC are hiring for Data Science jobs?

Cities near North Augusta, SC with the most Data Science job openings:

Data Science jobs near you
Infographic showing various Data Science job openings in North Augusta, SC as of August 2026, with employment types broken down into 1% As Needed, 77% Full Time, 19% Part Time, and 3% Contract. Highlights an 86% Physical, 2% Hybrid, and 12% Remote job distribution, with an average salary of $115,357 per year, or $55.5 per hour.

Data Scientist - multiple levels - CLEARANCE and POLYGRAPH REQUIRED

Constellation Technologies, Inc

Augusta, GA • On-site

$120K - $220K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Re-posted 5 days ago

Job description

Big Data, dataflows, Artificial Intelligence / Machine Learning (AI/ML) familiarity, Analytics in GME, Jupyter notebooks, and Spark.
 
Due to federal contract requirements, United States citizenship and an active TS/SCI security clearance and polygraph are required for the position.
 
 
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.
These Qualifications Would be Nice to Have:
  • Fully Cleared polygraph is preferred
  • Knowledge of working with Big Data, dataflows, Machine Learning/Artificial Intelligence familiarity.
  • Analytics in GME, Jupyter notebooks, and Spark.
$120,000 - $220,000 a year
The pay range for this job, with multi-levels, is a general guideline only and not a guarantee of compensation or salary. Additional factors considered in extending an offer include (but are not limited to) responsibilities of the job, education, experience, knowledge, skills, and abilities, as well as internal equity, alignment with market data, applicable bargaining agreement (if any), or other law.
The benefits package:
 
Affordable healthcare options with 80% employer paid premium PLUS a company-funded HSA
Dental insurance with 100% employer paid premium
Vision with 80% employer paid premium
Employer paid Life insurance 100%
Employer paid Short-term and Long-term disability 100%
Annual training, continued education, and professional memberships reimbursement
Unlimited access to Red Hat Enterprise Linux, AWS, and NetApp training and accreditation
Annual reimbursement for technology i.e. phones, computers, printers, etc...
401(k) with company match up to 5% with 100% immediate vesting (after 90 days of employment)
 
The environment and perks:
 
Professional development investment and paid time off for training
Contract and work locations in Maryland, Virginia, Colorado, Texas, Utah, California, Florida and Hawaii.
Team building events throughout the year such as Destination Family Events, Holiday Party, Monthly Get-Togethers
Leadership Team engagement and mentorship
Performance Recognition Program
Complimentary branded apparel
 
Don't see a job opening that's the perfect fit? Apply to our General Position to join our talent pool for consideration for future opportunities.
 
Know someone else who may be a good fit? Refer them through the CTI External Referral Program and you could receive a one-time referral bonus of up to $10,000! Email [email protected] for more information.
 
Constellation Technologies is an Equal Opportunity/Affirmative Action Employer. All qualified applicants will receive consideration for employment without regard to race, religion, creed, color, national origin, ancestry, sex (including pregnancy, childbirth, breastfeeding, or medical conditions related to pregnancy, childbirth, or breastfeeding), age, medical condition, marital or domestic partner status, sexual orientation, gender, gender identity, gender expression and transgender status, mental disability or physical disability, genetic information, military or veteran status, citizenship, low-income status or any other status or characteristic protected by applicable law. Job applicants can submit questions about CTI's equal employment opportunity policy to [email protected].
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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