Principal Applied Scientist

Elevance Health•Walnut Creek, CA

2d•$214,192 - $350,496•Hybrid

About The Position

The Principal Applied Scientist is responsible for leading the design, development, deployment, and scaling of advanced artificial intelligence and machine learning solutions that drive enterprise transformation and measurable business outcomes. Serves as a senior technical authority for artificial intelligence strategy, architecture, governance, and production implementation.

Requirements

Requires an MS or PhD in Computer Science, Machine Learning, Statistics, Applied Mathematics, Operations Research, Engineering, Data Science, Economics, or a related quantitative discipline and a minimum of 10 years of experience in machine learning, data science, artificial intelligence, advanced analytics, or related technical fields; or any combination of education and experience which would provide an equivalent background.
Experience leading artificial intelligence or machine learning initiatives from concept through production deployment required.
Experience with Python, machine learning frameworks, cloud-based artificial intelligence, or machine learning platforms, MLOps, model deployment, monitoring, lifecycle management, and structured and unstructured data systems required.

Nice To Haves

Experience with generative artificial intelligence, large language models, reinforcement learning, information retrieval, forecasting, recommender systems, optimization, causal inference, experimentation, or decision intelligence preferred.
Experience in healthcare, insurance, financial services, life sciences, or other regulated industries preferred.

Responsibilities

Defines and drives enterprise artificial intelligence and machine learning strategy aligned with organizational priorities.
Leads the design, validation, deployment, monitoring, and continuous improvement of advanced artificial intelligence and machine learning solutions.
Architects scalable end-to-end production systems, including model training, evaluation, deployment, monitoring, and lifecycle management.
Translates complex business challenges into scalable artificial intelligence solutions with measurable outcomes.
Establishes technical standards, reusable patterns, and best practices for enterprise artificial intelligence development and governance.
Partners with business and technology leaders to influence capability roadmaps and deliver sustainable business value.
Mentors data scientists, machine learning engineers, researchers, and technical leaders.