Senior Manager Applied Science

Job description

Job Description

Oracle Health AI (OHAI) is Oracle’s center of innovation for applying advanced artificial intelligence to the most critical challenges in healthcare and enterprise.

Leveraging Oracle’s extensive cloud resources and rich healthcare data assets, our multidisciplinary team of scientists, engineers, and clinicians develops leading-edge AI solutions—such as large language models and generative AI—that drive smarter decisions, automate workflows, and improve outcomes at scale.

At OHAI, we are dedicated to translating the latest breakthroughs in AI into practical, responsible, and impactful technology for clinicians, patients, and organizations worldwide.

We are seeking a visionary Senior Manager to lead the team to scalable, production-ready generative AI solutions in healthcare and enterprise domains.

As a people manager and technical leader, you will collaborate cross-functionally with product, engineering, and clinical teams, leveraging the latest advances in Generative AI to drive product development.

Responsibilities: 

Strategic Leadership & Vision

• Define and drive the AI research and development strategy for healthcare solutions, aligned with organizational goals and regulatory requirements.
• Identify opportunities where Gen AI can deliver measurable improvements in clinical workflows, patient workflows, and healthcare operations.
• Act as a thought leader, staying abreast of advances in AI, healthcare informatics, and regulatory landscapes, and translating them into actionable innovation roadmaps.

Team & Talent Development

• Lead, mentor, and grow a team of applied scientists, machine learning engineers, and data scientists to deliver impactful AI solutions.
• Foster a culture of innovation, scientific rigor, and collaboration across multidisciplinary teams including clinicians, product managers, and engineers.
• Provide career development guidance, performance management, and technical mentorship to elevate the team’s capabilities.

AI Solution Development & Delivery

• Oversee the end-to-end lifecycle of AI projects, from problem definition, data acquisition, and model development to deployment and monitoring in clinical or operational environments.
• Ensure models are built with high standards for accuracy, latency, fairness, explainability, and compliance with healthcare regulations (HIPAA, GDPR, FDA, TGA, etc.).
• Partner with product and engineering teams to translate research prototypes into production-ready, scalable, and reliable AI solutions.

Cross-Functional Collaboration

• Collaborate with clinicians, healthcare domain experts, and business stakeholders to ensure AI solutions address real-world pain points and integrate seamlessly into workflows.
• Communicate technical results, risks, and trade-offs effectively to executive leadership and non-technical stakeholders.

Impact Measurement

• Define success metrics for AI initiatives, ensuring outcomes are measured in terms of healthcare impact, operational efficiency, and business value.
• Continuously evaluate deployed models, leading efforts to monitor drift, drive improvements as needed and maintain product excellence over different stages of the product.

Qualifications and Experience: 

Education & Experience

• Master’s or PhD in AI/Gen AI, Machine Learning or related technical field.
• 5+ years of experience in AI/Gen AI or Machine Learning, with 1-3 years in a leadership/managerial role overseeing applied science or AI research teams.
• Have led a team size of 5+ members to deliver product releases.
  
  

Technical Expertise

• Proven track record of building and deploying AI or Gen AI solutions in production environments.
• Strong understanding of ML/DL/AI, NLP, computer vision, or multimodal learning as applied to different application domains.
• Hands-on experience as applied scientists delivering AI/Gen AI products, models, patents, and/or papers in the past.
  
  

Leadership & Collaboration

• Demonstrated ability to lead, mentor, and grow teams of applied scientists or machine learning engineers.
• Proven ability to thrive in fast-paced, ambiguous environments while maintaining scientific rigor and compliance discipline.
• Strong track record of cross-functional collaboration with domain experts, product managers, and engineering teams.
• Excellent communication skills with the ability to present complex technical concepts to both technical and non-technical stakeholders.
• Exceptional leadership presence and ability to influence at executive and board levels.

Preferred Qualifications

Medical domain Knowledge 

• Familiarity with healthcare standards and data formats (e.g., HL7, FHIR, DICOM, ICD-10, CPT).
• Experience working with clinical, claims, or operational healthcare datasets, with an understanding of privacy/security requirements (e.g., HIPAA, GDPR).

Operational & Business Acumen

• Strong business sense with the ability to connect AI innovation to healthcare ROI, patient outcomes, and strategic priorities.

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Qualifications

Career Level - M4

Required Skill Profession

Other Management Occupations