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Data Science Analytics Jobs in Georgia (NOW HIRING)

Maayee Inc

Analytics Lead / Data Scientist

Suwanee, GA · On-site

Qualifications Bachelor's or Master's degree in Data Science, Computer Science, Analytics, or related field. 5+ years of experience in analytics, data science, or business intelligence. Strong skills ...

Further

Data Science Analyst

Atlanta, GA · On-site

Required : • 2-5 years of professional experience in data science or advanced marketing analytics. • Strong command of R and/or Python for data manipulation and statistical analysis. • Deep ...

Further

Data Science Analyst

Atlanta, GA · On-site

What you bring: * 2-5 years of professional experience in data science or advanced marketing analytics. We value a background that combines marketing domain expertise with technical data science ...

Tror AI for everyone

Data Scientist

Atlanta, GA · On-site

Core Data Science & Analytics Demonstrate strong expertise in data exploration, feature engineering, statistical modeling, and predictive analytics, with the ability to operationalize models in ...

Truist

Decision Scientist II

Atlanta, GA · On-site

... data-driven insights powered by analytics in support of enhanced decision-making. Focus on continuous improvement in decision science delivery and outcomes in pursuit of business optimization. 4. ...

Deloitte

AI and Data Science Engineer III

Atlanta, GA · On-site

Responsibilities : • Lead the design, development, and delivery of analytics solutions that ... in data science, analytics, or a related field - with direct experience in client-facing or ...

Deloitte

AI and Data Science Engineer III

Atlanta, GA

$110K - $132K/yr

AI Data Science Engineer III Our Deloitte Human Capital team transforms technology platforms ... Lead the design, development, and delivery of analytics solutions that address complex workforce ...

Deloitte

AI and Data Science Engineer III

Atlanta, GA · On-site

$110K - $132K/yr

AI Data Science Engineer III Our Deloitte Human Capital team transforms technology platforms ... Lead the design, development, and delivery of analytics solutions that address complex workforce ...

Varsity Tutors

Data Science Tutor

Woodstock, GA · Remote

$40/hr

What We Look For In a Data Science Tutor * Advanced Subject Mastery ... Deep knowledge of statistical analysis, data wrangling, exploratory data analysis, machine learning ...

KPMG

Manager, Data Science

Atlanta, GA · On-site

KPMG is currently seeking a Manager, Data Science to join our Consulting practice. Responsibilities ... Translate advanced business analytics problems into technical approaches that yield actionable ...

Varsity Tutors

Data Science Tutor

Duluth, GA · Remote

$40/hr

What We Look For In a Data Science Tutor * Advanced Subject Mastery ... Deep knowledge of statistical analysis, data wrangling, exploratory data analysis, machine learning ...

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$46

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How much do data science analytics jobs pay per hour?

As of Jun 11, 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 are the key skills and qualifications needed to thrive as a Data Science Analytics professional, and why are they important?

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.

Is AI replacing data analysts?

AI is transforming the role of data analysts by automating routine tasks such as data cleaning and basic analysis, allowing analysts to focus on more complex insights and strategic decision-making. While AI tools can augment their work, human expertise remains essential for interpreting results, understanding context, and making nuanced judgments. Data analysts with skills in machine learning, programming, and data visualization are increasingly valuable in this evolving environment.

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 is the job of data science and analytics?

Data science and analytics involve collecting, processing, and analyzing large datasets to extract meaningful insights that support decision-making. Professionals in this field use statistical methods, programming tools like Python or R, and visualization techniques to identify trends, solve problems, and improve business outcomes.

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.

Is 40 too late for data science?

Data science analysts and professionals can enter the field at any age, including 40 or older. Success depends on acquiring relevant skills such as programming, statistics, and tools like Python or R, as well as gaining experience through projects or certifications. Age is less important than skills, continuous learning, and adapting to industry changes.

What jobs can you get with data science and analytics?

Data science and analytics skills open opportunities for roles such as data analyst, data scientist, business intelligence analyst, machine learning engineer, and data engineer. These positions typically require proficiency in programming languages like Python or R, statistical analysis, and data visualization tools, often within technology, finance, healthcare, or marketing industries.
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 are popular job titles related to Data Science Analytics jobs in Georgia? For Data Science Analytics jobs in Georgia, the most frequently searched job titles are:
What job categories do people searching Data Science Analytics jobs in Georgia look for? The top searched job categories for 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:
Data Science Analytics jobs near you
Analytics Lead / Data Scientist

Analytics Lead / Data Scientist

Maayee Inc

Suwanee, GA • On-site

Contractor

Posted 29 days ago

Job description

Location: Seattle, WA

Duration: 6-12 Months

We are seeking an Analytics Lead / Data Scientist to lead enterprise analytics, reporting, and data integration initiatives across a complex technology environment that includes IBM Maximo, Oracle Financials, SCADA, GIS, AMI, billing, customer service, and hybrid cloud/on-premises platforms.

This role will drive improvements in data quality, enterprise reporting, and advanced analytics to support operational efficiency and strategic decision-making.

Key Responsibilities

Lead analytics and business intelligence initiatives across enterprise systems.

Integrate and analyze data from multiple legacy and operational platforms.

Improve data quality, governance, and reporting capabilities.

Develop dashboards, KPIs, predictive models, and actionable insights.

Collaborate with business and IT teams to support data modernization efforts.

Mentor analytics team members and support data-driven decision-making.

Qualifications

Bachelor’s or Master’s degree in Data Science, Computer Science, Analytics, or related field.

5+ years of experience in analytics, data science, or business intelligence.

Strong skills in SQL, Python, data visualization, and BI tools such as Microsoft Power BI or Tableau.

Experience with enterprise systems, data integration, and cloud/on-premises environments.

Utility industry experience is preferred.

Apply