Senior AI/ML Scientist — Drive Global Impact

McKinsey; Atlanta (GA); On-site; USD 176,000 - 180,000; Full time

Benefits offered by this job

Competitive salary

World-class benefits

Global team environment

Job summary

McKinsey's QuantumBlack, AI by McKinsey is seeking a senior data scientist to lead the development of AI/ML solutions that solve complex business challenges across industries. You will mentor data scientists and shape the R&D roadmap, delivering end-to-end analytics products with real-world impact.

Based in North America, you will collaborate with data engineers, ML engineers, designers and product managers, leveraging Python, PySpark, Airflow, Databricks and cloud platforms to drive measurable

Qualifications

• Bachelors, master’s or PhD in computer science, ML, statistics, mathematics, engineering or AI.
• 6+ years of deep technical experience in distributed computing, ML and statistics.
• Proficiency in Python, R, Scala, SQL and data science methods.
• Knowledge of distributed computing or NoSQL is a plus.
• Strong client-facing and collaboration skills.

Responsibilities

• Lead development of AI/ML solutions delivering measurable impact.
• Mentor data scientists and shape the QuantumBlack roadmap.
• Collaborate with data engineers, ML engineers and designers on end-to-end analytics.
• Translate complex analytics into business value for clients.

Skills

Python

R

Scala

SQL

Machine Learning

Statistics

Leadership

Communication

Willingness to travel

Education

Bachelor's/Master's/PhD in CS/ML/AI/Engineering/Statistics

Tools

PySpark

Airflow

Databricks

Kedro

Docker

Kubernetes

AWS

GCP

Azure

Job description

McKinsey's QuantumBlack, AI by McKinsey is seeking a senior data scientist to lead the development of AI/ML solutions that solve complex business challenges across industries. You will mentor data scientists and shape the R&D roadmap, delivering end-to-end analytics products with real-world impact.

Based in North America, you will collaborate with data engineers, ML engineers, designers and product managers, leveraging Python, PySpark, Airflow, Databricks and cloud platforms to drive measurable