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Data Science Project Manager Jobs in Georgia (NOW HIRING)

AIG

Manager Data Science, GenAI

Atlanta, GA · On-site

The Manager of Data Science will oversee a team delivering generative AI solutions and collaborate with cross-functional teams to innovate and manage risk effectively. Responsibilities : • Oversee ...

Verizon

Principal Data Scientist

Alpharetta, GA · On-site

You will spearhead high-impact data science projects that revolutionize product personalization ... your manager. Employees are responsible for maintaining compliance with hybrid work policies.

Home Depot

Associate Data Scientist

Atlanta, GA · On-site

$56K - $56K/yr

Supports data science projects by conducting effective analysis to solve business problems ... This position reports to manager or above * This position has 0 direct reports Travel Requirements:

Home Depot

Associate Data Scientist

Atlanta, GA · On-site

$56K - $56K/yr

Supports data science projects by conducting effective analysis to solve business problems ... This position reports to manager or above * This position has 0 direct reports Travel Requirements:

APTIM

Environmental Project Manager

Atlanta, GA · On-site

Interpretation and evaluation of scientific data. * Provide technical support to projects in all ... Excellent time management skills and ability to manage multiple activities on an on-going basis by ...

Home Depot

Associate Data Scientist, Marketing

Atlanta, GA · On-site

$56K - $56K/yr

Supports data science projects by conducting effective analysis to solve business problems ... This position reports to manager or above * This position has 0 direct reports Travel Requirements:

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How much do data science project manager jobs pay per hour?

As of Jul 16, 2026, the average hourly pay for data science project manager in Georgia is $48.56, according to ZipRecruiter salary data. Most workers in this role earn between $42.02 and $56.83 per hour, depending on experience, location, and employer.

What is the hottest job of the 21st century?

Data Science Project Managers are in high demand due to the rapid growth of data-driven decision-making across industries. They oversee data projects, coordinate teams, and require skills in analytics tools, project management, and communication. The role is considered one of the most sought-after careers in the 21st century for its impact and earning potential.

What is a Data Science Project Manager?

A Data Science Project Manager is a professional who oversees and coordinates data science projects from inception to completion. They act as a bridge between technical data science teams and business stakeholders, ensuring that project goals align with organizational objectives. Responsibilities include planning project timelines, managing resources, mitigating risks, and communicating progress. They also help define project requirements, monitor deliverables, and ensure that outcomes meet quality standards. Strong communication, analytical, and organizational skills are essential for this role.

Is 40 too late for data science?

For a Data Science Project Manager, age is not a barrier to entering or advancing in the field. Success depends on skills, experience, and continuous learning, such as mastering tools like Python or R and understanding business needs, regardless of age.

Can data scientists make $300k?

Data scientists can earn $300,000 or more annually, especially with extensive experience, advanced skills in machine learning and big data tools, and roles in high-paying industries or senior management positions. Achieving this level often requires a combination of technical expertise, certifications, and leadership responsibilities.

How does a Data Science Project Manager typically collaborate with data scientists and stakeholders throughout a project?

A Data Science Project Manager acts as a bridge between technical teams and business stakeholders, ensuring clear communication of goals, timelines, and deliverables. They facilitate regular meetings to discuss project progress, address any obstacles, and realign priorities as needed. By translating business requirements into actionable tasks for data scientists and providing updates to stakeholders, they help ensure that projects stay on track and deliver value. Effective collaboration often involves balancing technical feasibility with business needs, managing expectations, and fostering a cooperative team environment.

What is the difference between Data Science Project Manager vs Data Analyst?

AspectData Science Project ManagerData Analyst
Required CredentialsOften requires a bachelor’s or master’s in data science, analytics, or related fields; project management certifications beneficialTypically holds a bachelor’s degree in statistics, mathematics, or related areas; certifications like Microsoft Excel or Tableau are common
Work EnvironmentLeads data science projects, collaborates with data scientists, engineers, and stakeholdersAnalyzes data sets, creates reports, visualizations, and supports decision-making
Employer & Industry UsageUsed in tech, finance, healthcare, and consulting firms managing data science initiativesFound across industries for data reporting, business intelligence, and operational analysis

In summary, a Data Science Project Manager oversees data science projects and manages teams, requiring project management skills and relevant certifications. A Data Analyst focuses on analyzing data and creating reports, with a more technical and analytical role. Both roles are essential in data-driven organizations but differ in scope and responsibilities.

What are the key skills and qualifications needed to thrive as a Data Science Project Manager, and why are they important?

To thrive as a Data Science Project Manager, you need a solid understanding of data science methodologies, project management principles, and usually a degree in computer science, statistics, or a related field. Familiarity with analytics tools (such as Python, R, SQL), project management software (like Jira or Trello), and certifications such as PMP or Agile/Scrum are often required. Strong leadership, communication, and problem-solving skills set top performers apart by enabling effective team coordination and stakeholder management. These competencies ensure projects are delivered on time, within scope, and generate actionable insights that drive business value.

Can a data scientist become a project manager?

Yes, a data scientist can become a project manager by developing skills in leadership, communication, and project planning. Gaining experience in managing teams, understanding project workflows, and obtaining certifications like PMP can facilitate this transition.
What are popular job titles related to Data Science Project Manager jobs in Georgia? For Data Science Project Manager jobs in Georgia, the most frequently searched job titles are:
What job categories do people searching Data Science Project Manager jobs in Georgia look for? The top searched job categories for Data Science Project Manager jobs in Georgia are:
What cities in Georgia are hiring for Data Science Project Manager jobs? Cities in Georgia with the most Data Science Project Manager job openings:
Data Science Project Manager jobs near you
Manager Data Science, GenAI

Manager Data Science, GenAI

AIG

Atlanta, GA • On-site

Full-time

Re-posted 2 days ago

AIG rating

8.4

Company rating: 8.4 out of 10

Based on 22 frontline employees who took The Breakroom Quiz

101st of 281 rated insurance

Job description

Job Summary:
AIG is a leading global insurance organization providing a wide range of property casualty insurance and other financial services. The Manager of Data Science will oversee a team delivering generative AI solutions and collaborate with cross-functional teams to innovate and manage risk effectively.
Responsibilities:
• Oversee the development and delivery of data science and generative AI solutions aligned with business requirements, monitor solutions in production.
• Develop technical delivery plans and execute them to ship solutions on time.
• Mentor and develop junior data scientists.
• Collaborate with cross-functional teams including product managers, engineers, and business leaders.
• Build evaluation frameworks to measure LLM effectiveness, ground-truth dataset quality, and guide the product development roadmap.
Qualifications:
Required:
• 7+ years of experience in a data science role—preferably in NLP—in an agile, production-oriented environment.
• 3+ years of experience managing teams of data scientists and/or engineers.
• 2+ years of hands-on experience building generative AI solutions: prompt engineering, RAG and agentic frameworks, validation pipelines, and observability and monitoring solutions.
• Ph.D. or Master's in Data Science, Computer Science, or a related field.
• Ability to thrive in a fast-paced, high-stakes environment.
• Clear communicator and effective collaborator within and across teams.
• Able to operate as both a hands-on practitioner and a people manager.
• Highly technical, with a strong bias for execution.
Preferred:
• Experience on the Palantir platform or demonstrated certification is preferred.
• Ontology Mastery: A strong understanding of Ontology—specifically how to map complex real-world data entities and relationships into a digital twin framework to power AI applications.
• Large-scale Data Infrastructure: Strong understanding of performance optimization in big data environments, with hands-on experience using distributed data processing frameworks such as Apache Spark or PySpark.
• Agentic Solution: Experience implementing advanced agentic architectures, such as autonomous agents capable of multi-step reasoning and decision-making or integrating agentic solutions with large-scale enterprise systems.
Company:
American International Group, Inc. (NYSE: AIG) is a leading global insurance organization. Founded in 1919, the company is headquartered in New York, NY, US, , with a team of 10001+ employees. The company is currently Late Stage.

What AIG employees say

Pay

Benefits

Hours and flexibility

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About AIG

Sourced by ZipRecruiter

American International Group, Inc. (AIG) is a leading global insurance organization. Building on 100 years of experience, today AIG member companies provide a wide range of property casualty insurance, life insurance, retirement solutions, and other financial services to customers in more than 80 countries and jurisdictions. These diverse offerings include products and services that help businesses and individuals protect their assets, manage risks and provide for retirement security.

Industry

Insurance services

Company size

10,000+ Employees

Headquarters location

New York, NY, US

Year founded

1919

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