Data Science Specialist - Social, Healthcare, and Public Entities

Data Science Specialist - Social, Healthcare, and Public Entities jobs in United States

McKinsey & Company

• +16 more
• $192K/yr - $192K/yr

Responsibilities

• 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

Preferred

• advanced degree is a plus
• experience in these sectors is a plus

Benefits

• Resources, mentorship, and opportunities to support leadership development.
• Continuous learning through a learning and apprenticeship culture, structured programs, and clear, actionable feedback.
• A voice from day one, with ideas and contributions valued.
• Opportunity to learn from colleagues across 65+ countries and over 100 nationalities, with diverse backgrounds and experiences.
• A comprehensive benefits package to support holistic well-being for you and your family.
• Apprenticeship, coaching, and exposure to accelerate your growth.
• Glassdoor
• 4.1
• Global management consulting for businesses, governments, and institutions.
• New York, New York, USA
• http://www.mckinsey.com
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Qualifications

• US citizenship required
• Bachelor's degree in computer science, statistics, mathematics, engineering, economics, data science, or a related quantitative field required
• 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
• 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
• Advanced degree is a plus
• Experience in these sectors is a plus

Required skills

• AI Fairness and Explainability, Agentic AI, Generative AI, Healthcare, Machine Learning, Optimization, Public Sector, Python, Qualitative Analysis, Quantitative Analysis, SQL, Social Sector, Statistical Modeling

Preferred skills

• advanced degree is a plus, experience in these sectors is a plus

Experience

• 4+ years