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Data Science Analytics Jobs in Georgia (NOW HIRING)

Data Scientist I (DSAP)

Alpharetta, GA · On-site

$59K - $98K/yr

The Insurance Analytics team are the trusted leaders in analytics excellence, delivering innovative, data-driven solutions through cutting-edge data science and strategic risk solutions to drive ...

Data Scientist I (DSAP)

Alpharetta, GA · On-site

$59K - $98K/yr

The Insurance Analytics team are the trusted leaders in analytics excellence, delivering innovative, data-driven solutions through cutting-edge data science and strategic risk solutions to drive ...

Data Scientist I (DSAP)

Alpharetta, GA · On-site

$59K - $98K/yr

The Insurance Analytics team are the trusted leaders in analytics excellence, delivering innovative, data-driven solutions through cutting-edge data science and strategic risk solutions to drive ...

Data Engineer

Augusta, GA · On-site

$100 - $115/hr

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

Data Engineer

Augusta, GA · On-site

$100K - $115K/yr

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

Data Engineer

Augusta, GA · On-site

$90K - $108K/yr

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

Data Engineer

Augusta, GA · On-site

$90K - $108K/yr

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

Data Engineer

Augusta, GA · On-site

$107K - $129K/yr

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

Learn and apply appropriate data science and data engineering techniques to solve business problems * Collaborate with data and analytics colleagues as well as key business stakeholders Work ...

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Showing results 41-60

Data Science Analytics information

See Georgia salary details

$20

$46

$79

How much do data science analytics jobs pay per hour?

As of Sep 5, 2026, the average hourly pay for data science analytics in Georgia is $46.23, according to ZipRecruiter salary data. Most workers in this role earn between $37.16 and $52.36 per hour, depending on experience, location, and employer.

What is data science analytics?

Data science analytics is the process of extracting insights and knowledge from data using statistical, mathematical, and computational techniques. It involves collecting, cleaning, analyzing, and visualizing data to help organizations make informed decisions. Professionals in this field use tools like Python, R, and SQL to interpret complex data sets, build predictive models, and identify trends or patterns. Data science analytics plays a key role in industries such as finance, healthcare, retail, and technology, enabling businesses to optimize operations and improve outcomes.

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

To thrive in Data Science Analytics, a strong background in statistics, data modeling, and programming (often with a degree in computer science, mathematics, or a related field) is essential. Familiarity with tools such as Python, R, SQL, and data visualization platforms like Tableau or Power BI, as well as knowledge of machine learning libraries, is typically required. Critical thinking, problem-solving, and effective communication skills help professionals translate complex data insights into actionable business strategies. These competencies are crucial for extracting meaningful information from data and driving informed decision-making within organizations.

How do data science analytics professionals typically collaborate with other departments within an organization?

Data science analytics professionals often work closely with teams across the organization, such as marketing, finance, product development, and IT. Their role involves understanding business needs, gathering requirements, and translating complex data findings into actionable insights for non-technical stakeholders. Effective communication and teamwork are essential, as data scientists may participate in cross-functional meetings, present their analyses, and tailor their recommendations to support strategic decision-making. This collaborative approach not only enhances the impact of analytics projects but also fosters continuous learning and innovation within the organization.

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

AspectData Science AnalyticsData Analyst
Required CredentialsDegree in Data Science, Statistics, or related fields; programming skillsDegree in Statistics, Mathematics, or related fields; proficiency in Excel and SQL
Work EnvironmentOften involves complex modeling, machine learning, and predictive analyticsFocuses on data cleaning, reporting, and visualization
Employer & Industry UsageTech companies, finance, healthcare, and research institutionsBusiness, marketing, finance, and operations across various industries

Data Science Analytics and Data Analysts both work with data, but Data Science Analytics typically involves advanced modeling and predictive techniques, while Data Analysts focus on data reporting and visualization. The roles often overlap, but Data Science Analytics requires more technical skills and a deeper understanding of algorithms.

What can I do with data science analytics?

Data science analytics involves analyzing large datasets to extract insights, support decision-making, and solve complex problems. Professionals in this field use tools like Python, R, and SQL, and often work in industries such as finance, healthcare, or marketing to develop predictive models and visualize data. Skills in statistics, machine learning, and data visualization are essential for success in this role.

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

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

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

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

Infographic showing various Data Science Analytics job openings in Georgia as of August 2026, with employment types broken down into 1% As Needed, 86% Full Time, 11% Part Time, and 2% Contract. Highlights an 84% Physical, 4% Hybrid, and 12% Remote job distribution, with an average salary of $96,153 per year, or $46.2 per hour.

Data Scientist - Delivery Data Science

Home Depot

Atlanta, GA • On-site

Full-time

Posted 29 days ago


Home Depot rating

7.4

Company rating: 7.4 out of 10

Based on 6,489 frontline employees who took The Breakroom Quiz

5th of 39 rated national retailers


Job description

With a career at The Home Depot, you can be yourself and also be part of something bigger.
Position Purpose:
The Data Scientist is responsible for supporting data science initiatives that drive business profitability, increased efficiencies and improved customer experience. This role applies industry-leading analytical methodologies for working with large datasets to extract meaningful business insight and creatively solve business problems. Data Scientists are also responsible for ensuring that developed codes are documented into a library of reusable algorithms. Based on the specific data science team, this role would need to be knowledgeable in one or more data science specializations, such as optimization, computer vision, recommendation, search or NLP.
As a Data Scientist, you will apply advanced analytics methods and algorithms for identifying trends and providing business solutions. This role is expected to present insights and recommendations to non-technical audiences and explain the benefits and impacts of the recommended solutions. In addition, Data Scientists collaborate with business partners and cross-functional teams, requiring effective communication skills, building relationships, and focus on understanding the overall business area being supported.
Key Responsibilities:
  • 55% Solution Development - Design and develop algorithms and models to use against large datasets to create business insights; Participates in large data analytics project teams by serving as a technical lead for analytics projects; May lead small projects and work independently on solution development; Execute tasks with high levels of efficiency and quality; Make appropriate selection, utilization and interpretation of advanced analytical methodologies
  • 20% Communicating Results - Effectively communicate insights and recommendations to both technical and non-technical leaders and business customers/partners; Present recommendations in a confident manner in order to influence execution of recommendation; Prepare reports, updates and/or presentations related to progress made on a project or solution; Clearly communicate impacts of recommendations to drive alignment and appropriate implementation
  • 10% Business Collaboration - Incorporate business knowledge into solution approach; Effectively develop trust and collaboration with internal customers and cross-functional teams; Work with project teams and business partners to determine project goals
  • 15% Technical Exploration & Development - Seek further knowledge on key developments within data science, technical skill sets, and additional data sources; Participate in the continuous improvement of data science and analytics by developing replicable solutions (for example, codified data products, project documentation, process flowcharts) to ensure solutions are leveraged for future projects; Build and maintain library of reusable algorithms for future use, ensuring developed codes are documented

Direct Manager/Direct Reports:
  • This position typically reports to Manager or above
  • This position has 0 Direct Reports

Travel Requirements:
  • Typically requires overnight travel less than 10% of the time.

Physical Requirements:
  • Most of the time is spent sitting in a comfortable position and there is frequent opportunity to move about. On rare occasions there may be a need to move or lift light articles.

Working Conditions:
  • Located in a comfortable indoor area. Any unpleasant conditions would be infrequent and not objectionable.

Minimum Qualifications:
  • Must be eighteen years of age or older.
  • Must be legally permitted to work in the United States.

Preferred Qualifications:
  • Masters in a quantitative field (Computer Science, Math, Statistics, etc.) or equivalent work experience
  • 4+ years of experience in business intelligence and analytics
  • Working knowledge of Microsoft Excel and Power Point
  • Experience in a modern scripting language (preferably Python)
  • Proficient running queries against data (preferably with Google BigQuery or SQL)
  • Proficient with data visualization software (preferably Tableau)
  • Proficient utilizing statistical techniques to identify key insights that help solve business problems
  • Knowledgeable in Prescriptive Modeling like optimization, computer vision, recommendation, search or NLP
  • Demonstrated experience in predictive modeling, data mining and data analysis

Minimum Education:
  • The knowledge, skills and abilities typically acquired through the completion of a bachelor's degree program or equivalent degree in a field of study related to the job.

Preferred Education:
  • No additional education

Minimum Years of Work Experience:
  • 3

Preferred Years of Work Experience:
  • No additional years of experience

Minimum Leadership Experience:
  • None

Preferred Leadership Experience:
  • None

Certifications:
  • None

Competencies:
  • Action Oriented: Taking on new opportunities and tough challenges with a sense of urgency, high energy, and enthusiasm
  • Business Insight: Applying knowledge of the business and the marketplace to advance the organization's goals
  • Collaborates: Building partnerships and working collaboratively with others to meet shared objectives
  • Communicates Effectively: Developing and delivering multi-mode communications that convey a clear understanding of the unique needs of different audiences
  • Customer Focus: Building strong customer relationships and delivering customer-centric solutions
  • Drives Results: Consistently achieving results, even under tough circumstances
  • Nimble Learning: Actively learning through experimentation when tackling new problems, using both successes and failures as learning fodder
  • Optimizes Work Processes: Knowing the most efficient and effective processes to get things done, with a focus on continuous improvement
  • Plans and Aligns: Planning and prioritizing work to meet commitments aligned with organizational goals
  • Self-Development: Actively seeking new ways to grow and be challenged using both formal and informal development channels

What Home Depot employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom


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About Home Depot

Sourced by ZipRecruiter

The Home Depot is the world’s largest home improvement specialty retailer, operating a vast network of warehouse-format stores across the United States, Canada, and Mexico. Founded in 1978, the company has established itself as the primary resource for building materials, lawn and garden products, and home décor. Its business model caters to two distinct customer bases: Do-It-Yourself (DIY) homeowners and "Pro" customers, such as professional contractors and tradespeople. Beyond product sales, the company offers an extensive suite of services, including professional installation and one of the largest tool rental operations in North America.

Industry

Retail, manufacturing and personal services

Company size

10,000+ Employees

Headquarters location

Atlanta, GA, US

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