Corporate Director, Data Science & AI Engineering

Overview

Be inspired.  Be rewarded. Belong. At Emory Healthcare. 

At Emory Healthcare we fuel your professional journey with better benefits, valuable resources, ongoing mentorship and leadership programs for all types of jobs, and a supportive environment that enables you to reach new heights in your career and be what you want to be.  We provide: 

• Comprehensive health benefits that start day 1 
• Student Loan Repayment Assistance & Reimbursement Programs 
• Family-focused benefits  
• Wellness incentives 
• Ongoing mentorship, development, and leadership programs  
• And more  

Ideally seeking an Atlanta based candidate able to visit our Atlanta based office, but may consider remote options in the following locations:  applicants residing in or able to relocate to the following states are eligible for hire: Alabama, Arkansas, Florida, Georgia, Illinois, Louisiana, Michigan, New Hampshire, North Carolina, Ohio, Pennsylvania, South Carolina, Tennessee, Texas, Virginia, and Wisconsin

Description

Emory Healthcare (EHC) — Georgia's most comprehensive academic health system — is investing boldly in its AI-powered data future. As we modernize our enterprise data platform on Microsoft Fabric and scale AI capabilities across clinical, research, and operational domains, we are searching for an exceptional leader to serve as Corporate Director, Data Science & AI Engineering.Dual reporting to the Chief Data & Analytics Officer (CDAO) and the Chief AI Officer (CAIO), this role is the connective tissue between enterprise strategy and AI/ML execution. You will own the data science management vision, lead a multidisciplinary team that includes AI Engineers and Data Scientists, and serve as the primary architect of how Emory Healthcare harnesses advanced machine learning, generative AI, and large-scale analytics to improve patient outcomes and institutional performance.This is not a theoretical strategy role. We expect our Director to be equally fluent in designing data Science and AI  frameworks, deploying ML models into production, overseeing LLMOps pipelines, and translating complex analytical findings into boardroom-ready strategy — all within a dynamic, mission-driven health system environment.  RESPONSIBILITIES:  Below is a comprehensive list of the areas this person will be leading: AI & Machine Learning Operations

• Provide strategic direction for the design, deployment, and lifecycle management of ML and AI models across clinical and operational use cases.

• Establish and mature MLOps and LLMOps practices — including model versioning, monitoring, drift detection, and responsible AI guardrails — in collaboration with AI Engineers.

• Champion the integration of Generative AI and large language model (LLM) capabilities into EHC workflows, identifying high-value use cases and ensuring safe, governed deployment.
• Partner with the CDAO and CAIO Offices and Emory Digital/OIT to build a scalable, cloud-native ML infrastructure on Microsoft Fabric and Azure, enabling rapid experimentation and production-grade AI delivery.

Data & Advanced Analytics Strategy

• Collaborate with the Corp Director AI Strategy, Corp Director Data Engineering, and Data & AI Governance Manager to obtain a deep understanding of stakeholder data needs across the Health System and translate those needs into a cohesive, institution-wide executable Data & AI Models.

• Catalog existing data shortcomings, establish common definitions, and lead initiatives to reduce reporting redundancies and increase data access, sharing, and consumption.

• Drive advanced analytics initiatives — including predictive modeling, NLP, and population health analytics — that directly inform strategic fundraising, clinical operations, and resource planning.

• Proactively mine all data sources for untapped opportunities; surface patterns through data modeling that enhance EHC's Digital Data & Analytics roadmap.

Data and AI Governance & Management

• Design and implement comprehensive data/AI governance policies, data quality frameworks, and data standards in collaboration with Emory partners.

• Own data lifecycle management strategy: ingestion, transformation, quality, archiving, and retention across structured and unstructured datasets.

• Work with legal, compliance, and IT to ensure data privacy (HIPAA, GDPR), ethical AI use, and responsible data stewardship practices are embedded in all programs.

• Lead the modernization of shared data management and analytics architecture, facilitating joint collaborations that leverage Fabric-based shared infrastructure and resources.<