Data Scientist, Consultant

Your Role

The AI & Machine Learning team works in partnership across the enterprise to accelerate business outcomes by applying machine learning, statistical analysis, generative AI, and applied AI to build intelligent products that create "intelligence at scale." Reporting to the Director, AI & Machine Learning, the Data Scientist, Consultant will develop and deploy novel applications that leverage machine learning models, statistical methods, and generative AI. This role focuses on rapidly developing new features and working across partner teams to deliver solutions and maximize impact, translating cutting-edge AI research into real-world products and taking features from 0 to 1. You will design, build, and ship production-grade AI products, including LLM-powered applications, AI agents and copilots, retrieval-augmented generation (RAG) and search, statistical models, and AI-enabled automation, embedded directly into customer-facing applications and enterprise workflows such as claims, payment integrity, clinical insights, and member experience.

Our leadership model is about developing great leaders at all levels and creating opportunities for our people to grow - personally, professionally, and financially. We are looking for leaders that are energized by creative and critical thinking, building and sustaining high-performing teams, getting results the right way, and fostering continuous learning.

Your Knowledge and Experience

Bachelor's degree in computer science, statistics, quantitative discipline, or equivalent practical experience

7 years of experience in software development, applied AI/ML, and statistical analysis

Demonstrated track record of building and shipping software products rapidly, not just developing models or analyses

Working knowledge of machine learning and statistical analysis methods, with experience applying these techniques to business problems

Strong software engineering skills and proficiency in Python, including building APIs and backend services

Experience with ML design and ML infrastructure, including model deployment, evaluation, and data processing, and working with machine learning frameworks and libraries

Hands-on experience with deep learning and LLM application frameworks, including PyTorch, TensorFlow, LangChain, and LangGraph

Hands-on experience building applications that leverage generative AI models, including prompt engineering and retrieval-augmented generation (RAG)

Preferred Knowledge and Experience

Master's degree; or a PhD with relevant experience

Experience with generative AI research or applications

Experience building agent-based systems and working with orchestration frameworks

Experience with cloud computing platforms and infrastructure (e.g., Azure, Google Cloud, or AWS), and scalable data processing with SQL or Spark

Solid MLOps and LLMOps practices, including CI/CD, monitoring, and model lifecycle management

Experience rapidly developing and shipping software in a fast-paced, customer-facing environment, adapting to changing priorities

Understanding of responsible AI and governance for regulated or healthcare environments

Hybrid

This role requires employees to be in-office based on our hybrid workplace model, balancing purposeful in-person collaboration with flexibility. For most teams, this means coming into the office two days each week.

Employees living more than 50 miles from an office location will work with their manager to determine in-office time based on business need.