Data Science & AI Consultant — Public Sector

McKinsey; Chicago (IL); On-site; USD 173,000 - 211,000; Full time

Benefits offered by this job

Competitive salary

Comprehensive benefits package

Job summary

McKinsey & Company is seeking a data science professional to work within the SHaPE practice, partnering with government agencies and healthcare/public sector clients. You will design and implement ML solutions, build data pipelines, and advise on AI adoption and responsible use across client engagements.

You will balance hands-on modeling with strategic guidance, translating technical results for non-technical stakeholders, and driving value while upholding high standards of ethics and

Qualifications

• Bachelor’s degree in a quantitative field required; advanced degree 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 curiosity about emerging methods, including generative AI and agentic AI

Responsibilities

• You will serve government agencies, public health and healthcare organizations, and social sector institutions and partner with clients at all levels.
• You will build data science and AI solutions and advise on adoption, value, and responsible use.
• You will translate client problems into ML problems, build data pipelines, train and evaluate models, and explore RAG and agentic AI techniques.

Skills

Python

SQL

Machine Learning

Education

Bachelor’s degree in a quantitative field

Job description

McKinsey & Company is seeking a data science professional to work within the SHaPE practice, partnering with government agencies and healthcare/public sector clients. You will design and implement ML solutions, build data pipelines, and advise on AI adoption and responsible use across client engagements.

You will balance hands-on modeling with strategic guidance, translating technical results for non-technical stakeholders, and driving value while upholding high standards of ethics and