Director, Applied Science

Oracle•United States,

12h•$169,800 - $355,400

About The Position

The Director, Applied Science partners with cross-functional leaders to identify and address strategic business and product needs through machine learning and artificial intelligence. The role leads teams and research programs across the full applied research lifecycle, from surveying state-of-the-art technologies and preparing high-quality datasets to running proofs of concept and experiments, designing and optimizing ML and AI models and solution architectures, and delivering solutions into production. The Director sets group standards and science strategy, guides research and development of innovative products and services, and ensures that research insights are interpreted and communicated across the organization. The role also supports operational readiness, drives cross-functional delivery, and builds the group's applied research expertise and presence in the research community through publications, presentations, paper reviews, and keynote speaking. As a senior organizational leader, the Director oversees complex projects and multiple teams, aligns resources and priorities with business needs, develops talent, promotes collaboration and continuous improvement, and works with HR on hiring and promotion processes.

Responsibilities

Partner with cross-functional leaders to identify strategic business and product needs related to machine learning and artificial intelligence.
Lead the group in setting quality standards and executing end-to-end science strategy to address product and business problems.
Direct research and development strategies for innovative products and services.
Set standards for developing and piloting research proofs of concept and experiments to demonstrate feasibility and secure support and funding for applied research.
Contribute to group-wide standards for selecting and preparing datasets, and ensure high-quality, comprehensive datasets are used across the organization.
Direct research programs that identify theories, tools, and methodologies and transfer state-of-the-art technologies into products and services or advance the field.
Define standards for designing, developing, and optimizing machine learning models, large language models, and generative AI technologies, including training, fine-tuning, and computation optimization.
Promote best practices for ML and AI solution architecture, including data, model, training, and evaluation.
Guide teams in extracting meaningful insights from data and metadata, interpreting findings, and communicating them throughout the organization.
Lead the creation of patents, white papers, and other technical documentation related to applied research.
Improve group processes for developing and maintaining efficient, bug-free code and organized codebases; promote best practices for version control, code review, and deployment.
Review professional documentation for technical processes, including experimentation, data collection and analysis, and model building.
Leverage resources to support operations, ensure successful solution delivery, and drive technical strategy.
Lead cross-functional initiatives that enable timely delivery and integration of services, and facilitate deployment into production environments.
Promote applied research excellence, build domain expertise, and ensure teams use research best practices.
Lead publication, presentation, and review of research findings and papers in top-tier conferences and research and industry outlets; serve as a keynote speaker at conferences or panels.
Oversee multiple teams managing complex projects or initiatives, including timelines, deliverables, and budgets when applicable; delegate work, set priorities, and adjust resources and timelines as business needs change.
Lead cross-functional collaboration and partnerships with business leaders, stakeholders, and customers; promote transparency, inclusivity, and consideration of diverse perspectives.
Share problem-solving strategies across teams, oversee complex operational and technical issues, and coach teams in analyzing complex information and identifying root causes.
Pursue strategic learning opportunities, develop team expertise, identify organizational skill gaps, promote knowledge-sharing, and evaluate learning strategies.
Empower teams to develop and implement process improvements, gain buy-in, seek feedback, and prioritize improvement initiatives aligned with strategic direction and return on investment.
Drive performance through feedback and coaching, promote consistent talent development and performance expectations, align development goals with organizational initiatives, and collaborate with HR on talent strategy, hiring, and promotions.