Sr. AI & Data Scientist

Role overview Lead the design and delivery of production machine learning systems for complex healthcare challenges. This senior individual contributor role spans problem discovery, technical architecture, model development, deployment, and ongoing performance improvement, with work focused on measurable outcomes for members. You will also guide technical practice across the data science team and help product, clinical, operations, and compliance partners turn opportunities into deployable solutions.

Responsibilities - Architect end-to-end ML solutions for applications such as risk stratification, clinical decision support, chart review, and fraud detection. - Select models and define system designs for multi-model workflows and real-time decision systems. - Own the ML lifecycle from experimentation and validation through deployment, monitoring, drift detection, and improvement. - Establish instrumentation, observability, alerts, and feedback loops to support reliable production services. - Apply current methods in deep learning, NLP and language models, computer vision, and causal inference; promote sound engineering practices. - Partner with business and clinical stakeholders, explain technical options in practical terms, and mentor data scientists through reviews and collaborative work.

Requirements - Five to eight years delivering production data science or ML solutions with demonstrated business impact. - A record of architecting complex ML systems from research through production deployment. - Deep expertise across multiple ML areas and strong software engineering fundamentals. - Experience leading technical projects and mentoring data scientists. - Advanced skills in machine learning, statistical analysis, experimental design, and MLOps. - Ability to understand healthcare claims, clinical, or member data and communicate technical findings to varied audiences.

Nice to have - Healthcare experience, particularly with Medicare Advantage, risk adjustment, or claims analytics. - Production document-understanding experience, including OCR, entity extraction, or language-model pipelines. - Research publications, patents, open-source work, or experience bringing research methods into production. - Familiarity with cloud platforms, healthcare regulations, distributed computing, streaming, or real-time inference.

Benefits and work setup The listed pay range is $172,364–$258,547. Pay may depend on factors including location, education, experience, and responsibilities.