Data Science Manager Jobs in Georgia
Data Science Manager jobs in Georgia are in strong demand, concentrated in financial services, logistics, health systems, and technology, with openings at every level from team lead to senior director. Atlanta anchors the market, followed by activity in Alpharetta and Savannah, with major employers such as Home Depot, Delta Air Lines, and Emory Healthcare consistently hiring across machine learning, analytics engineering, and product-focused data science. Candidates with hands-on experience leading teams and fluency in cloud-based data infrastructure are the most sought-after. Find a role that fits below and apply directly.
Find Data Science Manager JobsOverview
Open roles25
Top employerThe Home Depot
Top cityAtlanta, GA
Cities hiring3
Work type75% On-site
Top industryInsurance
Showing 5 of 25+ Data Science Manager jobs
Data Science Specialist - Social, Healthcare, and Public Entities
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Added 4d ago
McKinsey & Company
Data Science Specialist - Social, Healthcare, and Public Entities
Atlanta, Georgia
Added 4d ago
Data Science and Business Analytics Intern
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Added 5d ago
Mativ
Data Science and Business Analytics Intern
Alpharetta, Georgia
Added 5d ago
Senior Manager, Go-to-Market Data Science
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Added 1w ago
UCB
Senior Manager, Go-to-Market Data Science
Atlanta, Georgia
Added 1w ago
2027 Summer Intern - Data Science
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Added 2w ago
Papa John's
2027 Summer Intern - Data Science
Atlanta, Georgia
Added 2w ago
AI and Data Science Engineer III
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Added 3w ago
Deloitte
AI and Data Science Engineer III
Atlanta, Georgia
Added 3w ago
Added 4d ago
Data Science Specialist - Social, Healthcare, and Public Entities
McKinsey & Company·Atlanta, Georgia
Job functions:
Bachelor's degree in statistics
Job Description
Job ID: 113849
You will be part of our Social, Healthcare, and Public Entities (SHaPE) practice and work in teams of consultants, data scientists, data engineers, and industry experts.
- Atlanta
- Boston
- Charlotte
- Chicago
- Connecticut - Darien
- Dallas
- Denver
- Houston
- Miami
- New Jersey
+ 7 More
Do you want to do work that matters, alongside supportive leaders who will help you grow faster than you ever thought possible? Are you a creative problem-solver who is energized by challenges? You’ve come to the right place.
YOUR IMPACT
You will serve government agencies (including defense and national security organizations), public health and healthcare organizations, and social sector institutions and will partner with clients at all levels, from technical teams to senior leaders.
You will build data science and artificial intelligence (AI) solutions for our clients, and you will advise them on how to use data science well. You can expect half of your work to be hands-on technical work, and the other half will be helping clients decide where data science and AI can create value, what it takes to adopt them, and how to use them responsibly.
On the technical side, you will translate client problems into machine learning problems (for example, classification, forecasting, anomaly detection, or optimization), and select approaches based on the available data, the value at stake, and the solution requirements. This work includes building data pipelines and engineering features from structured and unstructured data, including text and documents. Using appropriate validation methods and metrics, you will train, tune, and evaluate supervised and unsupervised models, such as gradient-boosted trees, time-series models, and neural networks. Your work will also encompass building generative AI and agentic AI solutions, including retrieval-augmented generation (RAG), tool-using agents, and multi-step workflows, and evaluating them for accuracy, reliability, and safety.
To move models from prototype to production, you will apply MLOps and LLMOps practices, such as version control, experiment tracking, testing, and monitoring. Throughout this work, you will validate your own results, document assumptions and limitations, and test for bias, drift, and failure modes.
On the advisory side, you will help clients assess their data and analytics maturity, identify the highest-value use cases, and shape data science and AI strategies, roadmaps, and operating models. By explaining technical results to non-technical audiences and translating analytical outputs into recommended actions, you will help clients put insights into practice. Your advisory work will also address data governance, fairness, explainability, and the appropriate use of AI in public-facing settings. To ensure results last after our teams leave, you will help clients build their own data science capabilities.
YOUR GROWTH
Driving lasting impact and building long-term capabilities with our clients is not easy work. You are the kind of person who thrives in a high performance/high reward culture - doing hard things, picking yourself up when you stumble, and having the resilience to try another way forward.
In return for your drive, determination, and curiosity, we'll provide the resources, mentorship, and opportunities you need to become a stronger leader faster than you ever thought possible. Your colleagues—at all levels—will invest deeply in your development, just as much as they invest in delivering exceptional results for clients. Every day, you'll receive apprenticeship, coaching, and exposure that will accelerate your growth in ways you won’t find anywhere else.
When you join us, you will have:
- Continuous learning: Our learning and apprenticeship culture, backed by structured programs, is all about helping you grow while creating an environment where feedback is clear, actionable, and focused on your development. The real magic happens when you take the input from others to heart and embrace the fast-paced learning experience, owning your journey.
- A voice that matters: From day one, we value your ideas and contributions. You’ll make a tangible impact by offering innovative ideas and practical solutions, all while upholding our unwavering commitment to ethics and integrity. We not only encourage diverse perspectives, but they are critical in driving us toward the best possible outcomes.
- Global community: With colleagues across 65+ countries and over 100 different nationalities, our firm’s diversity fuels creativity and helps us come up with the best solutions for our clients. Plus, you’ll have the opportunity to learn from exceptional colleagues with diverse backgrounds and experiences.
- World-class benefits: On top of a competitive salary (based on your location, experience, and skills), we provide a comprehensive benefits package to enable holistic well-being for you and your family.
YOUR QUALIFICATIONS AND SKILLS
- US citizenship required
- Bachelor's degree in computer science, statistics, mathematics, engineering, economics, data science, or a related quantitative field required; advanced degree is a plus (if you are less than 8 years out of undergrad, please include your GPA on your resume)
- 4+ years of professional or academic experience applying machine learning, statistical modeling, or optimization to real problems
- Proficiency in Python and SQL; foundations in machine learning and statistical modeling, and curiosity about emerging methods, including generative AI and agentic AI
- Interest in the public, healthcare, or social sectors; experience in these sectors is a plus
- Demonstrated aptitude for both quantitative and qualitative analysis
- A quality and risk mindset: you check your own work, document assumptions and limitations, and think carefully about fairness, explainability, and the appropriate use of AI
- Ability to explain complex technical ideas clearly, both verbally and in writing, to technical and non-technical audiences
- Proven record of leadership at work or through extracurricular activities
- Ability to work collaboratively in a team and effectively with people at all levels of an organization
- Commitment to high standards and core values
- Willingness to travel up to 80%
Please review the additional requirements regarding essential job functions of McKinsey colleagues.
Our unwavering commitment to integrity drives everything we do, guiding us to always act in the best interests of our clients, our people, and the communities we serve.
McKinsey & Company
Data Science Specialist - Social, Healthcare, and Public Entities
Atlanta, Georgia
Added 4d ago
Job functions:
Bachelor's degree in statistics
Job Description
Job ID: 113849
You will be part of our Social, Healthcare, and Public Entities (SHaPE) practice and work in teams of consultants, data scientists, data engineers, and industry experts.
- Atlanta
- Boston
- Charlotte
- Chicago
- Connecticut - Darien
- Dallas
- Denver
- Houston
- Miami
- New Jersey
+ 7 More
Do you want to do work that matters, alongside supportive leaders who will help you grow faster than you ever thought possible? Are you a creative problem-solver who is energized by challenges? You’ve come to the right place.
YOUR IMPACT
You will serve government agencies (including defense and national security organizations), public health and healthcare organizations, and social sector institutions and will partner with clients at all levels, from technical teams to senior leaders.
You will build data science and artificial intelligence (AI) solutions for our clients, and you will advise them on how to use data science well. You can expect half of your work to be hands-on technical work, and the other half will be helping clients decide where data science and AI can create value, what it takes to adopt them, and how to use them responsibly.
On the technical side, you will translate client problems into machine learning problems (for example, classification, forecasting, anomaly detection, or optimization), and select approaches based on the available data, the value at stake, and the solution requirements. This work includes building data pipelines and engineering features from structured and unstructured data, including text and documents. Using appropriate validation methods and metrics, you will train, tune, and evaluate supervised and unsupervised models, such as gradient-boosted trees, time-series models, and neural networks. Your work will also encompass building generative AI and agentic AI solutions, including retrieval-augmented generation (RAG), tool-using agents, and multi-step workflows, and evaluating them for accuracy, reliability, and safety.
To move models from prototype to production, you will apply MLOps and LLMOps practices, such as version control, experiment tracking, testing, and monitoring. Throughout this work, you will validate your own results, document assumptions and limitations, and test for bias, drift, and failure modes.
On the advisory side, you will help clients assess their data and analytics maturity, identify the highest-value use cases, and shape data science and AI strategies, roadmaps, and operating models. By explaining technical results to non-technical audiences and translating analytical outputs into recommended actions, you will help clients put insights into practice. Your advisory work will also address data governance, fairness, explainability, and the appropriate use of AI in public-facing settings. To ensure results last after our teams leave, you will help clients build their own data science capabilities.
YOUR GROWTH
Driving lasting impact and building long-term capabilities with our clients is not easy work. You are the kind of person who thrives in a high performance/high reward culture - doing hard things, picking yourself up when you stumble, and having the resilience to try another way forward.
In return for your drive, determination, and curiosity, we'll provide the resources, mentorship, and opportunities you need to become a stronger leader faster than you ever thought possible. Your colleagues—at all levels—will invest deeply in your development, just as much as they invest in delivering exceptional results for clients. Every day, you'll receive apprenticeship, coaching, and exposure that will accelerate your growth in ways you won’t find anywhere else.
When you join us, you will have:
- Continuous learning: Our learning and apprenticeship culture, backed by structured programs, is all about helping you grow while creating an environment where feedback is clear, actionable, and focused on your development. The real magic happens when you take the input from others to heart and embrace the fast-paced learning experience, owning your journey.
- A voice that matters: From day one, we value your ideas and contributions. You’ll make a tangible impact by offering innovative ideas and practical solutions, all while upholding our unwavering commitment to ethics and integrity. We not only encourage diverse perspectives, but they are critical in driving us toward the best possible outcomes.
- Global community: With colleagues across 65+ countries and over 100 different nationalities, our firm’s diversity fuels creativity and helps us come up with the best solutions for our clients. Plus, you’ll have the opportunity to learn from exceptional colleagues with diverse backgrounds and experiences.
- World-class benefits: On top of a competitive salary (based on your location, experience, and skills), we provide a comprehensive benefits package to enable holistic well-being for you and your family.
YOUR QUALIFICATIONS AND SKILLS
- US citizenship required
- Bachelor's degree in computer science, statistics, mathematics, engineering, economics, data science, or a related quantitative field required; advanced degree is a plus (if you are less than 8 years out of undergrad, please include your GPA on your resume)
- 4+ years of professional or academic experience applying machine learning, statistical modeling, or optimization to real problems
- Proficiency in Python and SQL; foundations in machine learning and statistical modeling, and curiosity about emerging methods, including generative AI and agentic AI
- Interest in the public, healthcare, or social sectors; experience in these sectors is a plus
- Demonstrated aptitude for both quantitative and qualitative analysis
- A quality and risk mindset: you check your own work, document assumptions and limitations, and think carefully about fairness, explainability, and the appropriate use of AI
- Ability to explain complex technical ideas clearly, both verbally and in writing, to technical and non-technical audiences
- Proven record of leadership at work or through extracurricular activities
- Ability to work collaboratively in a team and effectively with people at all levels of an organization
- Commitment to high standards and core values
- Willingness to travel up to 80%
Please review the additional requirements regarding essential job functions of McKinsey colleagues.
Our unwavering commitment to integrity drives everything we do, guiding us to always act in the best interests of our clients, our people, and the communities we serve.
See All 25 Data Science Manager Jobs in Georgia
Find roles in Georgia that match your experience and apply in just a few clicks.
Find Data Science Manager JobsData Science Manager Jobs by City in Georgia
Where Georgia roles are concentrated, by current openings.
Data Science Manager Job Market in Georgia
A snapshot from current Georgia openings, updated as new roles post.
Who's Hiring
Top Industries Hiring
- Insurance
- Distribution & Wholesale
- Retail
- Consulting & Professional Services
What Georgia Employers Look For
The qualifications that appear most often in data science manager jobs across Georgia.
- Bachelor's or master's degree in data science, statistics, computer science, or a related field
- Five or more years of data science experience with at least two years managing a team
- Proficiency in Python or R, SQL, and cloud platforms such as AWS, Azure, or GCP
- Demonstrated experience translating business problems into data science solutions and roadmaps
- Familiarity with machine learning frameworks and model deployment in production environments
- Strong communication skills for presenting findings and strategy to non-technical stakeholders
Data Science Manager Jobs in Georgia: Frequently Asked Questions
How do you become a data science manager in Georgia?
Data science manager roles in Georgia do not require a state-issued license or registration. Most employers expect a bachelor's degree in a quantitative field such as statistics, computer science, or mathematics, with a master's degree preferred at larger organizations. Candidates typically build several years of hands-on data science experience, then move into management by leading projects or mentoring junior analysts. Georgia's large employer base in finance, logistics, and healthcare means applied domain experience in one of those industries is a meaningful differentiator.
Which companies hire data science managers in Georgia?
Employers hiring data science managers in Georgia right now include The Home Depot, AIG, and McKinsey & Company, based on current listings on Migrate Mate as of November 2026. Georgia's mix of Fortune 500 headquarters, major health systems, and a growing technology corridor in metro Atlanta means consistent demand across multiple industries throughout the year.
Which Georgia cities have the most data science manager jobs?
Atlanta, Kennesaw, and Alpharetta have the most data science manager openings in Georgia. Atlanta's concentration of corporate headquarters in retail, financial services, and logistics drives the bulk of demand, while Alpharetta and Savannah attract openings tied to technology campuses and growing port-adjacent supply-chain operations, respectively.
Are there remote data science manager jobs in Georgia?
Yes, and more than most fields. About 25% of data science manager openings tied to Georgia are remote or hybrid as of November 2026, reflecting how much of the work centers on analysis, model development, and team coordination rather than on-site presence. Strategy, stakeholder reporting, and pipeline management are the functions most commonly performed fully remotely.
How can I get hired as a data science manager in Georgia with little or no experience?
The most realistic entry path is moving into a team-lead role within a data science or analytics function after demonstrating individual contributor impact. Georgia employers such as large health systems, Tier 1 retailers headquartered in Atlanta, and financial services firms regularly promote senior analysts into player-coach manager roles. Starting as a senior data scientist or analytics lead, then volunteering to mentor others or own a cross-functional project, is the clearest on-ramp. A portfolio of end-to-end projects and Georgia Tech's OMSA credential both strengthen candidacy at this transition point.
Where can I find and apply to data science manager jobs in Georgia?
You can find and apply to data science manager jobs in Georgia on Migrate Mate, which lists current Georgia openings across industries and experience levels. Search the listings, find roles that fit your background, and apply directly to the ones that match.
See All 25 Data Science Manager Jobs in Georgia
Find roles in Georgia that match your experience and apply in just a few clicks.
Find Data Science Manager Jobs