Data Scientist

DataJobs; Atlanta (GA); On-site; USD 45,000 - 65,000; Full time

Benefits offered by this job

Continuous learning

Mentorship

Apprenticeship support

Competitive salary

Well-being benefits

World-class benefits

Job summary

McKinsey & Company invites students to join its data science apprenticeship in Atlanta, onsite. You’ll work on advanced analytics and AI initiatives, translating business questions into analytical problems and developing solutions across ML, optimization, GenAI, and agentic AI systems.

Collaboration with QuantumBlack and AI by McKinsey offers mentorship and growth. Upcoming graduates (Dec 2026–Aug 2027) with degrees in CS/ML/ statistics/engineering/AI are sought, along with Python and SQL

Qualifications

• Upcoming graduation between December 2026 and August 2027 with a Master’s, Bachelor’s, or PhD in computer science, machine learning, applied statistics, mathematics, engineering, artificial intelligence, or a related field
• Professional experience applying machine learning, statistical modeling, optimization, or GenAI techniques to real business problems
• Proficiency in Python and SQL, including the Python AI stack

Responsibilities

• Translate business challenges into analytical problems and develop and evaluate solutions across supervised, unsupervised, statistical, and forecasting approaches (with guidance)
• Apply basic evaluation methods for prompts, RAG models, or agents; document assumptions and limitations
• Support quality and risk practices, including growing awareness of fairness, explainability, and human oversight considerations
• Follow software development and MLOps/LLMOps best practices with guidance, including introductory exposure to CI/CD and agentic engineering concepts

Skills

Python

SQL

GenAI

Machine learning

Statistical modeling

Optimization

RAG models

LLMs

MLOps

CI/CD

Agentic AI

Education

Master’s, Bachelor’s, or PhD in CS/ML/Applied statistics/Math/Engineering/AI

Tools

Python stack tooling

Job description

McKinsey & Company brings an apprenticeship and learning culture that helps you build advanced analytics and AI solutions alongside experienced data scientists and engineers. If you’re a current student, this full-time opportunity is designed to accelerate your growth through coaching, exposure, and mentorship across a global Data Science community.

Location: Atlanta, GA (onsite)

What you’ll build

As a core member of a multidisciplinary team, you’ll work on advanced analytics and AI initiatives that address complex business challenges across industries. You’ll translate business questions into analytical problems, then develop and evaluate solutions spanning machine learning, optimization, GenAI, and agentic AI systems.

• Collaborate across QuantumBlack, AI by McKinsey, and QuantumBlack Labs to help clients harness advanced analytics and AI to improve decisions, transform operations, and build new capabilities
• Contribute to analytical workstreams and expand expertise across a breadth of industries and technologies
• With guidance, help select and implement analytical approaches while maintaining rigorous standards for data quality and evaluation
• Gradually take on increasing ownership to deliver solutions that are robust and fit for purpose

Selected examples of projects

• Develop an agentic AI solution to automate complex claims workflows for a global insurance company
• Optimize schedule and funding for a multi-billion-dollar capital project to accelerate delivery
• Use predictive modeling and agentic AI to improve customer service outcomes for a global travel company
• Build a digital twin of an automotive supply chain to enhance product availability
• Build client-facing capability by connecting analytical work with business needs across technical and business stakeholders

Core responsibilities

• Translate business challenges into analytical problems and develop and evaluate solutions across supervised, unsupervised, statistical, and forecasting approaches (with guidance)
• Apply basic evaluation methods for prompts, RAG models, or agents; document assumptions and limitations
• Support quality and risk practices, including growing awareness of fairness, explainability, and human oversight considerations
• Follow software development and MLOps/LLMOps best practices with guidance, including introductory exposure to CI/CD and agentic engineering concepts

What you bring

• Upcoming graduation between December 2026 and August 2027 with a Master’s, Bachelor’s, or PhD degree in computer science, machine learning, applied statistics, mathematics, engineering, artificial intelligence, or a related field
• Professional experience applying machine learning, statistical modeling, optimization, or GenAI techniques to real business problems
• Proficiency in Python and SQL, including the Python AI stack
• Foundational understanding of optimization, simulation, and decision logic, with the ability to apply methodologies with guidance
• Developing familiarity with Generative AI tools and simple agentic AI frameworks, with eagerness to learn how LLMs automate defined tasks
• Ability to manage time effectively in a complex, largely autonomous environment
• Willingness to travel
• Strong communication skills in English and local office language(s>, with the ability to adjust style for different perspectives and seniority levels

Technologies you’ll work with

Python, SQL, GenAI, machine learning, statistical modeling, optimization, RAG models, LLMs, agentic AI frameworks, MLOps, LLMOps, CI/CD, agentic engineering

Benefits

• Continuous learning through a learning and apprenticeship culture, backed by structured programs
• Mentorship and opportunities to become a stronger leader faster
• Apprenticeship, coaching, and exposure
• Competitive salary (based on location, experience, and skills)
• Comprehensive benefits package to enable holistic well-being for you and your family
• World-class benefits

Your growth at McKinsey is supported by apprenticeship, coaching, and exposure, with a structured learning culture that emphasizes clear, actionable feedback and a commitment to ethics and integrity.