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Weekend Machine Learning Jobs in Atlanta, GA (NOW HIRING)

This role requires strong expertise in advanced analytics, machine learning, statistical modeling, and data engineering principles. The ideal candidate is a strategic thinker who can translate ...

In this role, you will develop and deploy modern machine learning and AI models directly in our core product to address key customer challenges. We are looking for someone passionate about the full ...

In this role, you will develop and deploy modern machine learning and AI models directly in our core product to address key customer challenges. We are looking for someone passionate about the full ...

In this role, you will develop and deploy modern machine learning and AI models directly in our core product to address key customer challenges. We are looking for someone passionate about the full ...

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

Position Summary As a Data Scientist, you will be responsible for developing and implementing machine learning models and analytical solutions that support our water utility intelligence platform.

Position Summary As a Data Scientist, you will be responsible for developing and implementing machine learning models and analytical solutions that support our water utility intelligence platform.

Data Scientist

Atlanta, GA · On-site

$95 - $110/hr

Founded in 2005, we combine deep expertise in pricing and revenue management with modern software, machine learning, and AI to power complex commercial decisions. In Hospitality, we are building ...

Agentic AI Engineer

Atlanta, GA · On-site

$110K - $132K/yr

... machine learning models for classification, regression, NLP, or computer vision tasks. • Write clean, efficient, and well-documented Python code for data preprocessing, model training, and ...

Lead Data Scientist

Atlanta, GA · Remote

$166K - $214K/yr

Development of machine learning models and other analytics following established workflows, while also looking for optimization and improvement opportunities * Data annotation and quality review

Development of machine learning models and other analytics following established workflows, while also looking for optimization and improvement opportunities * Data annotation and quality review

AI/ML Engineer

Atlanta, GA

$110K - $132K/yr

Experienced AI/ML Engineer with expertise in Machine Learning, Deep Learning, NLP,and Generative AI. strong expertise in LLMs, Retrieval-Augmented Generation (RAG),Agentic AI, and MLOps to develop ...

Showing results 41-60

Weekend Machine Learning information

What are the most commonly searched types of Machine Learning jobs in Atlanta, GA?

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Cities near Atlanta, GA with the most Weekend Machine Learning job openings:

Data Scientist 2 4P/187

4P Consulting Inc.

Atlanta, GA

Contractor

Re-posted 17 days ago


Job description

Data Scientist (5–10 Years Experience)
Overview:

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 requires advanced analytics, machine learning expertise, and strong problem-solving skills to extract actionable intelligence from large and complex datasets.


Key Responsibilities:

1. Data Analysis:

  • Collect, clean, and analyze complex datasets to uncover trends, patterns, and actionable insights.

  • Apply statistical techniques to derive meaningful information for business strategies.

2. Predictive Modeling:

  • Develop and deploy machine learning models to forecast future trends, behaviors, and outcomes.

  • Utilize techniques such as regression analysis, classification, and clustering.

3. Data Visualization:

  • Create compelling visualizations using tools like Tableau, Power BI, and Python libraries (e.g., Matplotlib, Seaborn).

  • Effectively communicate insights to both technical and non-technical stakeholders.

4. Hypothesis Testing:

  • Formulate and test hypotheses to statistically validate business decisions and recommendations.

5. Feature Engineering:

  • Engineer and select relevant features to optimize the performance of machine learning models.

6. Algorithm Development:

  • Build and fine-tune machine learning algorithms such as decision trees, random forests, and neural networks.

7. Data Integration:

  • Collaborate with IT and database administrators to access and integrate data from multiple sources and data warehouses.

8. Model Deployment:

  • Deploy machine learning models into production environments to support real-time analytics and decision-making.

9. A/B Testing:

  • Design and evaluate A/B tests to assess the impact of process or product changes.

10. Data Ethics:

  • Ensure data handling practices meet ethical standards, including privacy and compliance with regulations.

11. Cross-functional Collaboration:

  • Work closely with engineers, business analysts, and domain experts to align data initiatives with business goals.

12. Mentorship:

  • Provide guidance and mentorship to junior data scientists and analysts to support team development.

13. Continuous Learning:

  • Stay updated on the latest data science tools, trends, and best practices through professional development.


Qualifications:
  • Education: Bachelor’s degree in a quantitative field (e.g., Computer Science, Statistics, Mathematics, Engineering).
    Master’s or Ph.D. is a plus.

  • Experience: 5 to 10 years in data science, with experience in machine learning and statistical analysis.

  • Programming Languages & Tools: Proficiency in Python, R, or Julia.

  • Visualization Tools: Experience with Tableau, Power BI, and Python visualization libraries (Matplotlib, Seaborn).

  • Database Skills: Strong understanding of databases and SQL-based data manipulation.

  • Additional Skills:

    • Advanced problem-solving and critical thinking abilities.

    • Strong communication skills for conveying technical findings to diverse audiences.

    • Familiarity with big data and distributed computing frameworks (e.g., Hadoop, Spark) is a plus.

    • Awareness of data ethics and regulatory compliance.