Data Science Specialist - Social, Healthcare, and Public Entities

You will be part of our Social, Healthcare, and Public Entities (SHaPE) practice and work in teams of consultants, data scientists, data engineers, and industry experts.

• Atlanta
• Boston
• Charlotte
• Chicago
• Connecticut - Darien
• Dallas
• Denver
• Houston
• Miami
• New Jersey

Do you want to do work that matters, alongside supportive leaders who will help you grow faster than you ever thought possible? Are you a creative problem-solver who is energized by challenges?
You've come to the right place.

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.

Driving lasting impact and building long‑term capabilities with our clients is not easy work. You are the kind of person who thrives in a high performance/high reward culture - doing hard things, picking yourself up when you stumble, and having the resilience to try another way forward.

In return for your drive, determination, and curiosity, we'll provide the resources, mentorship, and opportunities you need to become a stronger leader faster than you ever thought possible. Your colleagues-at all levels-will invest deeply in your development, just as much as they invest in delivering exceptional results for clients. Every day, you'll receive apprenticeship, coaching, and exposure that will accelerate your growth in ways you won't find anywhere else.

When you join us, you will have:

• Continuous learning: Our learning and apprenticeship culture, backed by structured programs, is…