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University of Maryland Global Campus · 3 months ago

Director, Data Science and AI/ML

(North America) Adelphi, MD

Full-time

Hybrid

Director/Executive

$193K/yr - $218K/yr

10+ years exp

The University of Maryland Global Campus is seeking an experienced Director of Data Science and AI/ML to lead their data science and machine learning initiatives. This role involves overseeing a team, driving the implementation of MLOps and AIOps processes, and collaborating with business stakeholders to deliver AI/ML solutions aligned with business objectives.

EdTechEducationHigher EducationUniversities

H1B Sponsor Likely

Responsibilities

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

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

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

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

Qualification

Data ScienceMachine LearningMLOpsDatabricksAIDeep LearningPythonSQLGraphRAGLeadershipCommunicationCollaborationProblem Solving

Required

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

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

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)

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

Preferred

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

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

Benefits

Generous Time Off: Enjoy 22 days of paid vacation, 15 days of sick leave, 3 personal days, and 15 paid holidays (16 during general election years). For part-time employees, time off rates will be prorated based on the number of hours worked.

Comprehensive Health Coverage: Access to health care, medical with vision, dental, and prescription plans for both individuals and families, effective from the 1st of the month following your hire date.

Insurance Options: Term Life Insurance, Accidental Death and Dismemberment Insurance, and Long-Term Disability (LTD) Insurance. Part-time employees working less than 0.5 FTE are not eligible for LTD.

Flexible Spending Accounts: Available for medical and dependent care expenses.

Retirement Plans: Choose between the Optional Retirement Program (ORP) or the Maryland State Retirement and Pension System (MSRPS).

Supplemental Retirement Plans: include 401(k), 403(b), 457(b), and various Roth options. The university does not provide matching funds.

Tuition Remission: Immediate availability for Regular Exempt Staff. Spouses and dependent children are eligible for undergraduate tuition remission after two years of service. NOTE: For part-time employees (at least 50 percent of the time), tuition remission benefits are prorated.

Company

University of Maryland Global Campus

Glassdoor3.5

The University of Maryland Global Campus is a public university focused on online education and headquartered in Adelphi, Maryland.

Founded in 1947

Hyattsville, Maryland, USA

1001-5000 employees

https://www.umgc.edu/index.cfm

H1B Sponsorship

University of Maryland Global Campus has a track record of offering H1B sponsorships. Please note that this does not guarantee sponsorship for this specific role. Below presents additional info for your reference. (Data Powered by US Department of Labor)

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2025 (1)