Public Sector Data Scientist: AI, ML & Advisory

McKinsey; Charlotte (NC); On-site; USD 173,000 - 211,000; Full time

Benefits offered by this job

Healthcare benefits

Retirement plan

Paid time off

Parental leave

Job summary

McKinsey & Company seeks a data science professional to work across SHaPE in building AI solutions for government, health, and social sector clients. You will split time between hands-on modeling and advising on data strategy, governance, and responsible AI.

You will translate business problems into ML tasks, develop data pipelines, and apply MLOps, all while guiding clients on adoption and value realization. Collaboration across teams is essential.

Qualifications

• US citizenship required.
• Bachelor's degree in computer science, statistics, mathematics, engineering, economics, data science, or a related quantitative field.
• 4+ years applying machine learning, statistical modeling, or optimization to real problems.
• Proficiency in Python and SQL; foundations in ML and statistics; curiosity about emerging methods.
• Interest in public, healthcare, or social sectors; ability to explain complex ideas clearly.
• Leadership experience and ability to work collaboratively across levels.
• Willingness to travel up to 80%.

Responsibilities

• Serve government agencies, public health and healthcare organizations, and social sector institutions.
• Build data science and AI solutions; half time hands-on technical work, half advisory.
• Translate client problems into ML problems; build data pipelines and features.
• Apply MLOps and LLMOps; validate results, monitor bias and drift.
• Advise on data governance, fairness, explainability, and responsible AI use.
• Help clients develop data science capabilities for lasting impact.

Skills

Python

SQL

ML fundamentals

Explainability

Education

Bachelor's degree in a quantitative field

Advanced degree preferred

Job description

McKinsey & Company seeks a data science professional to work across SHaPE in building AI solutions for government, health, and social sector clients. You will split time between hands-on modeling and advising on data strategy, governance, and responsible AI.

You will translate business problems into ML tasks, develop data pipelines, and apply MLOps, all while guiding clients on adoption and value realization. Collaboration across teams is essential.