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Data Insight Jobs in Georgia (NOW HIRING)

A Data Scientist with 5 to 10 years of experience is responsible for leveraging data to uncover insights, create predictive models, and drive data-driven decision- making within an organization.

Use AI driven insights to accelerate problem discovery, hypothesis validation, prioritization, and decision making. Partner with engineering and data science teams to embed AI assistance directly ...

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 ...

This role requires hands on experience with cloud native solutions to meet the complex Data and Insights requirements of our customers, while increasingly leveraging modern AI native, Copilot driven ...

The ideal candidate will be interpreting and analyzing complex datasets to provide insights and support data-driven decision making within Blue Bird. This role will work alongside IT business ...

The ideal candidate will be interpreting and analyzing complex datasets to provide insights and support data-driven decision making within Blue Bird. This role will work alongside IT business ...

The ideal candidate will be interpreting and analyzing complex datasets to provide insights and support data-driven decision making within Blue Bird. This role will work alongside IT business ...

The ideal candidate will be interpreting and analyzing complex datasets to provide insights and support data-driven decision making within Blue Bird. This role will work alongside IT business ...

The ideal candidate will be interpreting and analyzing complex datasets to provide insights and support data-driven decision making within Blue Bird. This role will work alongside IT business ...

The successful candidate will turn data into information, information into insight and insight into business decisions. Data analyst responsibilities include conducting a full lifecycle analysis to ...

The successful candidate will turn data into information, information into insight and insight into business decisions. Data analyst responsibilities include conducting a full lifecycle analysis to ...

Key Responsibilities Data Analysis & Insight Generation * Collect, clean, and analyze complex datasets * Identify trends, patterns, and actionable insights * Apply statistical techniques to support ...

Data Engineer

Atlanta, GA · On-site

$100K - $130K/yr

Develops and maintains data engineering best practices and contributes to Insights on data analytics and visualization concepts, methods and techniques. * Works closely with the data science and ...

Data Engineer

Atlanta, GA · On-site

$100K - $130K/yr

Develops and maintains data engineering best practices and contributes to Insights on data analytics and visualization concepts, methods and techniques. * Works closely with the data science and ...

Experience in creating, collecting, analysing and communicating business insights from data ... Experience working on metrics such as retention, churn, engagement and marketing analytics.

Data Engineer

Atlanta, GA · On-site

$100K - $130K/yr

Develops and maintains data engineering best practices and contributes to Insights on data analytics and visualization concepts, methods and techniques. * Works closely with the data science and ...

Our Data Scientist will be responsible for supporting data science initiatives that drive business ... Effectively communicate insights and recommendations to both technical and non-technical leaders ...

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Showing results 1-20

Data Insight information

See Georgia salary details

$38.8K

$139.3K

$205.6K

How much do data insight jobs pay per year?

As of May 31, 2026, the average yearly pay for data insight in Georgia is $139,338.00, according to ZipRecruiter salary data. Most workers in this role earn between $112,700.00 and $143,500.00 per year, depending on experience, location, and employer.

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

To thrive as a Data Insight professional, you need strong analytical skills, statistical knowledge, and a background in data science or a related field. Proficiency in data analysis tools such as SQL, Python, R, and visualization platforms like Tableau or Power BI, along with relevant certifications, is typically required. Exceptional problem-solving abilities, business acumen, and effective communication skills help translate complex data into actionable insights. These capabilities are critical for driving data-driven decisions and generating measurable business value.

How does a Data Insight professional typically collaborate with other departments within an organization?

Data Insight professionals frequently work cross-functionally, partnering with teams such as marketing, product, finance, and operations to translate raw data into actionable business strategies. They often participate in meetings to understand stakeholder goals, gather requirements, and present their findings through clear reports or visualizations. Effective communication and the ability to tailor insights for non-technical audiences are crucial, as these professionals help bridge the gap between data analysis and strategic decision-making across the company.

What are Data Insight professionals?

Data Insight professionals are experts who analyze and interpret data to uncover valuable trends, patterns, and actionable information that help organizations make informed decisions. They use various analytical tools and techniques to transform raw data into meaningful insights that can drive business strategies, optimize operations, and solve complex problems. Their work typically involves collecting, cleaning, and processing data, as well as presenting findings to stakeholders in a clear and impactful way.

What is the difference between Data Insight vs Data Analyst?

AspectData InsightData Analyst
Required CredentialsTypically a degree in data science, analytics, or related fields; certifications like Tableau, Power BIOften a degree in statistics, mathematics, or related fields; certifications in Excel, SQL, or analytics tools
Work EnvironmentCollaborates with business teams to provide strategic insights; may work in tech, finance, marketingAnalyzes data sets, prepares reports, and visualizations; works across various industries
Employer & Industry UsageUsed by companies seeking actionable insights for decision-makingEmployed in diverse sectors for data analysis and reporting

Data Insight professionals focus on deriving strategic insights from data to inform business decisions, often working closely with stakeholders. Data Analysts primarily analyze data sets, create reports, and visualize data to support operational and strategic needs. While both roles require analytical skills and familiarity with data tools, Data Insights roles tend to emphasize strategic thinking and business impact, whereas Data Analysts focus on data processing and reporting.

Infographic showing various Data Insight job openings in Georgia as of May 2026, with employment types broken down into 94% Full Time, 1% Part Time, 1% Temporary, and 4% Contract. Highlights an 31% Physical, and 69% Remote job distribution, with an average salary of $139,338 per year, or $67 per hour.

DATA SCIENTIST

4P Consulting Inc.

Forest Park, GA • On-site

Contractor

Posted 6 days ago


Job description

HI,

Hope you're doing well

This is pankaj from 4P Consulting Please see below job description

Please share your resume if you're interested and have 5-10 years of experience submission on W2 basis only NO C2C

  • A Data Scientist with 5 to 10 years of
    experience is responsible for leveraging
    data to uncover insights, create predictive
    models, and drive data-driven decision-
    making within an organization.
  • This role
    involves advanced analytics, machine
    learning, and strong problem-solving skills
    to extract actionable information from
    large datasets. Key Responsibilities: Data
    Analysis: Collect, clean, and analyze
    complex datasets to identify trends,
    patterns, and actionable insights.
  • Use
    statistical techniques to uncover
    meaningful information from data.
    Predictive Modeling: Develop and deploy
    machine learning models to predict future
    trends, behaviors, and outcomes. Apply
    regression analysis, clustering,
    classification, and other modeling
    techniques.
  • Data Visualization: Create
    compelling data visualizations to
    communicate findings effectively to both
    technical and non-technical stakeholders
    using tools like Tableau, Power BI, or
    Python libraries. Hypothesis Testing:
    Formulate and test hypotheses, providing
    statistical validation for business
    decisions and recommendations.
  • Feature
    Engineering: Engineer and select relevant
    features for machine learning models,
  • enhancing their predictive power.
    Algorithm Development: Build and fine-
    tune machine learning algorithms, such
    as decision trees, random forests, neural
    networks, and more, depending on the
    specific problem.
  • Data Integration:
    Collaborate with IT and database
    administrators to integrate and access
    data from various sources and data
    warehouses. Model Deployment: Deploy
    machine learning models in production
    environments to support real-time
    decision-making. A/B Testing: Design and
    analyze A/B tests to measure the impact
    of changes and improvements. Data
    Ethics:
  • Ensure ethical data practices,
    including privacy and compliance with
    data protection regulations. Cross-
    functional Collaboration: Collaborate with
    cross-functional teams, including
    engineers, business analysts, and domain
    experts, to understand business
    requirements and align data science
    initiatives with organizational goals.
    Mentorship:
  • Provide guidance and
    mentorship to junior data scientists and
    analysts, fostering their professional
    growth. Continuous Learning: Stay
    updated on the latest data science tools,
    techniques, and trends through ongoing
    professional development. Qualifications:
    Bachelors degree in a quantitative field
    (e.g., Computer Science, Statistics,
    Mathematics, Engineering); a Masters or
    Ph.D. is a plus.
  • 5 to 10 years of experience
    in data science, including machine
    learning and statistical analysis.
    Proficiency in data analysis tools and
    programming languages such as Python,
    R, or Julia. Strong knowledge of machine
    learning algorithms and their applications.
    Experience with data visualization toolslike Tableau, Power BI, or data
    visualization libraries in Python (e.g.,
    Matplotlib, Seaborn). Solid understanding
    of databases and data manipulation using
    SQL. Excellent problem-solving and
    critical thinking skills. Strong
    communication skills to convey complex
    findings and insights to both technical and
    non-technical stakeholders. Familiarity
    with big data technologies and distributed
    computing frameworks is a plus (e.g.,
    Hadoop, Spark). Knowledge of data
    ethics, privacy, and compliance
    considerations.
  • A Data Scientist with 5 to
    10 years of experience is a critical asset to
    an organization, capable of transforming
    data into actionable insights, building
    predictive models, and driving data-driven
    decision-making. This role requires a
    strong foundation in data science
    techniques, programming, and advanced
    analytics, as well as the ability to
    collaborate with various teams and
    mentor junior staff.

Thanks and Regards

Sr. Talent Acquisition Specialist

Pankaj Mishra

Pankaj.Mishra@4pconsultinginc.com

+1 205-756-4834