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Data Scientist Machine Learning Jobs in Georgia (NOW HIRING)

Data Scientist Location: Johns Creek GA (Hybrid) . Job Summary We are seeking a highly analytical ... The ideal candidate will leverage statistical analysis, machine learning, and data mining ...

Following the machine learning lifecycle, the data scientist should be able to convert the results into actionable product recommendations to present internally and externally. What you'll be doing:

Summary The Data Scientist position is in the Logicpath division within Loomis. We are a team of ... The ideal candidate combines strong statistical and machine learning expertise with practical ...

Summary The Data Scientist position is in the Logicpath division within Loomis. We are a team of ... The ideal candidate combines strong statistical and machine learning expertise with practical ...

Summary The Data Scientist position is in the Logicpath division within Loomis. We are a team of ... The ideal candidate combines strong statistical and machine learning expertise with practical ...

Summary The Data Scientist position is in the Logicpath division within Loomis. We are a team of ... The ideal candidate combines strong statistical and machine learning expertise with practical ...

Following the machine learning lifecycle, the data scientist should be able to convert the results into actionable product recommendations to present internally and externally. What you'll be doing:

Summary The Data Scientist position is in the Logicpath division within Loomis. We are a team of ... The ideal candidate combines strong statistical and machine learning expertise with practical ...

Data Scientist

Atlanta, GA · On-site

$80 - $100/hr

Data Scientist I The Data Scientist I provides data science, statistical, and advanced analytical ... Apply machine learning, artificial intelligence (AI), predictive modeling, and prescriptive ...

Data Scientist Opportunity This is Pankaj from 4P Consulting. Please see below Please share your ... Develop and deploy machine learning models to predict future trends, behaviors, and outcomes. Apply ...

Data Scientist

Atlanta, GA · On-site

$80 - $100/hr

Data Scientist I The Data Scientist I provides data science, statistical, and advanced analytical ... Apply machine learning, artificial intelligence (AI), predictive modeling, and prescriptive ...

Following the machine learning lifecycle, the data scientist should be able to convert the results into actionable product recommendations to present internally and externally. They will lead ...

Data Scientist

Atlanta, GA · On-site

$90K - $95K/yr

Data Scientist I The Data Scientist I provides data science, statistical, and advanced analytical ... Apply machine learning, artificial intelligence (AI), predictive modeling, and prescriptive ...

Following the machine learning lifecycle, the data scientist should be able to convert the results into actionable product recommendations to present internally and externally. They will lead ...

Data Scientist Opportunity This is Pankaj from 4P Consulting. Please see below Please share your ... Develop and deploy machine learning models to predict future trends, behaviors, and outcomes. Apply ...

Position Summary As a Senior Data Scientist, you will be responsible for designing and implementing machine learning models and data-driven solutions that enhance our water utility intelligence ...

Develop and deploy machine learning models to predict future trends, behaviors, and outcomes. Apply regression analysis, clustering, classification, and other modeling techniques. * Data ...

Showing results 21-40

Data Scientist Machine Learning information

See Georgia salary details

$31.7K

$103.6K

$165.9K

How much do data scientist machine learning jobs pay per year?

As of Sep 7, 2026, the average yearly pay for data scientist machine learning in Georgia is $103,638.00, according to ZipRecruiter salary data. Most workers in this role earn between $83,200.00 and $114,800.00 per year, depending on experience, location, and employer.

What is a data scientist machine learning?

A Data Scientist specializing in Machine Learning (ML) uses statistical methods, algorithms, and computational power to analyze data and create predictive models. They work with large datasets to identify patterns, train machine learning models, and improve decision-making processes. Responsibilities often include data cleaning, feature engineering, model selection, and performance evaluation. They may collaborate with engineers and business teams to deploy models in real-world applications. Strong skills in programming (Python, R), ML frameworks (TensorFlow, Scikit-learn), and data visualization are essential.

What are the typical day-to-day responsibilities of a data scientist machine learning?

On a typical day, a Data Scientist specializing in Machine Learning might gather and preprocess data, design and implement machine learning models, and evaluate their performance to solve real-world problems. They often collaborate with data engineers, software developers, and business stakeholders to translate business objectives into technical solutions and integrate models into existing systems. Other responsibilities can include visualizing data insights, conducting experiments to tune algorithms, and staying current with new developments in the field. The work is highly collaborative and iterative, requiring clear communication with various teams to ensure project goals are met efficiently.

What are the key skills and qualifications needed to thrive in the data scientist machine learning position, and why are they important?

To excel as a Data Scientist Machine Learning, you need a strong proficiency in statistics, programming (typically Python or R), and a solid understanding of machine learning algorithms, usually backed by a degree in computer science, mathematics, or a related field. Familiarity with tools such as TensorFlow, scikit-learn, SQL databases, and cloud platforms, as well as certifications in data science or machine learning, is commonly expected. Analytical thinking, problem-solving skills, and effective communication are vital soft skills in this profession. These qualifications combine to drive impactful insights and enable the successful development and deployment of machine learning models in business environments.

What is the salary of data scientist in machine learning?

The salary of a data scientist specializing in machine learning typically ranges from $90,000 to $150,000 annually, depending on experience, location, and industry. Senior roles or those with advanced skills in programming, statistical analysis, and tools like Python or TensorFlow may earn higher compensation.

What are the most commonly searched types of Data Scientist Machine Learning jobs in Georgia?

The most popular types of Data Scientist Machine Learning jobs in Georgia are:

What are popular job titles related to Data Scientist Machine Learning jobs in Georgia?

For Data Scientist Machine Learning jobs in Georgia, the most frequently searched job titles are:

What cities in Georgia are hiring for Data Scientist Machine Learning jobs?

Cities in Georgia with the most Data Scientist Machine Learning job openings:

Infographic showing various Data Scientist Machine Learning 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 $103,638 per year, or $49.8 per hour.

Data Scientist

VeeRteq Solutions Inc.

Johns Creek, GA • On-site

Contractor

This job post has expired today. Applications are no longer accepted.


Job description

Job description

Job Title: Data Scientist
Location: Johns Creek GA (Hybrid) .
 

Job Summary

We are seeking a highly analytical and motivated Data Scientist to join our team. The ideal candidate will leverage statistical analysis, machine learning, and data mining techniques to derive actionable insights from complex datasets. The candidate will work closely with business stakeholders, data engineers, and product teams to develop predictive models, optimize business processes, and support data-driven decision-making.

Key Responsibilities
  • Analyze large, complex datasets to identify trends, patterns, and business opportunities.
  • Develop, validate, and deploy machine learning and statistical models.
  • Design and implement predictive and prescriptive analytics solutions.
  • Perform data cleaning, feature engineering, and exploratory data analysis (EDA).
  • Collaborate with cross-functional teams to understand business requirements and translate them into analytical solutions.
  • Create dashboards, visualizations, and reports to communicate findings effectively.
  • Monitor model performance and continuously improve model accuracy and efficiency.
  • Conduct A/B testing and hypothesis testing to support business initiatives.
  • Work with structured and unstructured data from multiple sources.
  • Stay updated on emerging data science, AI, and machine learning technologies and best practices.
Required Skills & Qualifications
  • Bachelor's or Master's degree in Data Science, Computer Science, Statistics, Mathematics, Engineering, or a related field.
  • Strong proficiency in Python and/or R.
  • Experience with SQL and database technologies.
  • Hands-on experience with machine learning libraries such as Scikit-Learn, TensorFlow, PyTorch, or XGBoost.
  • Strong understanding of statistics, probability, and predictive modeling.
  • Experience with data visualization tools such as Tableau, Power BI, or Matplotlib.
  • Knowledge of cloud platforms such as AWS, Azure, or GCP.
  • Experience with big data technologies such as Spark, Hadoop, or Databricks is a plus.
  • Excellent problem-solving, communication, and stakeholder management skills.
Preferred Qualifications
  • Experience in healthcare, life sciences, finance, retail, or relevant industry domains.
  • Knowledge of Generative AI, LLMs, NLP, and MLOps frameworks.
  • Experience deploying machine learning models in production environments.
  • Familiarity with Git, CI/CD pipelines, Docker, and Kubernetes.