"Director, Data Science and AI/ML"

Director, Data Science and AI/ML

Company: University of Maryland Global Campus

Job Location: Adelphi, 20783

Category: IT Manager/Director

Type: Full-Time

Director, Data Science and AI/ML Data Strategy US Exempt Regular Full time Stateside Exempt 4.4 Location: Adelphi, MD (Hybrid)

The selected candidate for this position will report on-site 2-3 days a week.

We are seeking an experienced and dynamic Director of Data Science and AI/ML to lead our data science, AI and machine learning initiatives within a fast-paced, data-driven organization. This role demands a blend of deep technical expertise in machine learning, AI, and data engineering, combined with strong business acumen and strategic leadership. You will build and oversee a team of data scientists, AI, and machine learning engineers, guiding end-to-end solution delivery-from ideation, specification, and model development to scalable deployment, operationalization, monitoring, and continuous improvement-primarily leveraging Databricks.

As a hands-on leader, you will balance strategic vision with direct technical involvement, driving the implementation of robust MLOps and AIOps processes that ensure reliability, efficiency, and continuous improvement of AI/ML solutions in production. A key aspect of your role will be building trust and credibility with both business stakeholders and technical teams to foster collaboration, alignment, and shared success.

Duties and Responsibilities:

Leadership & Strategy

• Define and execute the vision and roadmap for data science, AI, and ML capabilities aligned with business objectives.
• Lead, mentor, and grow a high-performing team of data scientists and ML engineers, fostering collaboration, trust, and continuous learning.
• Collaborate with cross-functional business leaders to identify, prioritize, and formalize AI/ML use cases and requirements, producing both formal and evolving specification and operational documents.
• Establish best practices, processes, and governance for model development, deployment, and lifecycle management, including AIOps and MLOps workflows.
• Lead User Acceptance Testing (UAT) processes, ensuring delivered solutions meet business needs and quality standards.
• Champion iterative continuous improvement cycles, balancing innovation with risk management and consistent value delivery.
• Build strong relationships and gain trust with business and technical teams by demonstrating transparency, reliability, and responsiveness.

Technical Oversight & Hands-on Contribution

• Oversee the end-to-end AIOPs & MLOps lifecycle on Databricks, including data ingestion, feature engineering, model development, validation, deployment, and continuous monitoring.
• Lead the design, implementation, and refinement of MLOps pipelines and AIOps frameworks on Databricks to automate experimentation, deployment, versioning, monitoring, and alerting of models in production.
• Implement infrastructure and tooling for automated model testing, rollback, and retraining triggered by performance degradation or data drift, ensuring operational robustness and scalability.
• Ensure seamless collaboration between data scientists (focused on algorithm/model innovation and validation) and ML engineers (focused on scalable deployment, optimization, and MLOps infrastructure).
• Develop and enforce structured model handover contracts covering performance metrics, latency, memory footprint, and operational constraints to ensure smooth transitions from development to production teams.
• Participate hands-on in performance optimization, code reviews, and troubleshooting of AI/ML solutions in production environments.

Collaboration & Communication

• Foster a culture of transparency and teamwork, promoting close collaboration between data scientists, AI/ML engineers, software engineers, and business stakeholders.
• Communicate complex technical concepts and AI/ML performance and value insights effectively to technical and non-technical audiences.
• Engage proactively with stakeholders to manage evolving requirements and expectations.
• Build and maintain trust with diverse teams by being approachable, dependable, and delivering on commitments.
• Manage stakeholder expectations and project timelines within a SAFe Agile environment while balancing innovation with operational excellence.

Innovation & Continuous Improvement

• Stay abreast of emerging trends and technologies in AI, machine learning, MLOps, and AIOps, applying them strategically to maintain competitive advantage.
• Demonstrate quick learning aptitude to continuously incorporate new tools, methods, and industry best practices while leveraging opportunities and managing risks.
• Drive continuous model refinement post-deployment, leveraging live data and active learning techniques enabled by AIOps automation.
• Promote experimentation culture and data-driven decision making across the organization.

Skills:

Technical Skills

• Expertise in data science, AI, machine learning, and deep learning with proficiency in Python, SQL, and ML/DL frameworks (e.g., Scikit-learn, PyTorch, TensorFlow).
• Hands-on experience with Databricks environment including Unity Catalog, MLflow, Mosaic, AI/BI, Spark, Python.
• Experience working with Knowledge Graphs, GraphRAG, and AI Agents with MCP.
• Proven experience in designing and implementing MLOps pipelines covering experiment tracking, model versioning, CI/CD for ML, deployment automation, and model monitoring.
• Experience architecting and operationalizing AIOps processes for automated monitoring, alerting, anomaly detection, and automated remediation of AI/ML system failures or data drift.
• Experience leading formal and evolving requirements gathering and translating them into actionable specifications.
• Demonstrated ability to lead User Acceptance Testing (UAT) and iterative continuous improvement cycles.
• Familiarity with model serving frameworks (TFServing, TorchServe, ONNX) and experiment tracking tools (Neptune.ai, Comet.ml, Weights & Biases).

Business & Leadership Skills

• Strong business acumen with the ability to translate complex business problems into enterprise grade solution implementations.
• Demonstrated ability to lead and inspire technical teams, with experience managing cross-disciplinary groups.
• Excellent communication, presentation, and stakeholder management skills.
• Skilled at balancing strategic thinking with hands-on execution.
• Ability to foster a collaborative environment, resolve conflicts effectively, and gain trust from both business and technical teams.
• Quick learner with a strong awareness of emerging technologies, associated risks, and the imperative to deliver tangible business value.

Education & Experience Requirements:

Education:

• Bachelor's Degree in Information Science, Computer Science, Engineering, Mathematics, Statistics, or related STEM field.

Experience:

• 10+ years of experience in data science, machine learning, or AI, with at least three years in a leadership or managerial role.
• Proven track record of delivering AI/ML solutions in a production environment, ideally within large-scale cloud and Databricks ecosystems.
• Experience implementing scalable and robust MLOps and AIOps processes and tooling including Knowledge Graphs and GraphRAG.
• Experience working across the full AI/ML lifecycle from model development to production deployment and monitoring.
• Previous experience bridging the gap between data science, AI/ML, and data engineering teams to create seamless workflows.

Preferred Requirements:

Education:

• Master's Degree in Information Science, Computer Science, Engineering, Mathematics, Statistics, or related STEM field.

Experience:

• Passion for innovation, continuous learning in AI/ML, and operational excellence.
• Strong problem-solving mindset with a pragmatic approach.
• Ability to thrive in a dynamic, fast-paced environment and manage multiple priorities.
• Experience with advanced analytics, synthetic data generation, and data annotation strategies is a plus.

All submissions should include a cover letter and resume.

Hiring Range:

$193,000.00 - $218,000.00