AIML Data Scientist

Hi, Folks, Hope you're doing well. Role Title: AI/ML Data Scientist Engagement Type: Data Science & AI Enablement for Banner & Enterprise Systems Location: Remote Role Summary Seeking an AI/ML Data Scientist to support GMU in leveraging data across Banner and integrated systems to drive predictive insights, automation, and data-driven decision-making. This role will focus on developing machine learning models, analyzing institutional data, and enabling AI use cases aligned with student success, operational efficiency, and strategic planning. Key Responsibilities Data Analysis & Modeling Analyze data from Banner (Student, HR, Finance) and integrated systems Develop predictive models for use cases such as enrollment forecasting, student retention, and operational optimization Perform exploratory data analysis (EDA) to identify trends, anomalies, and insights Machine Learning Development Design, build, and validate ML models using Python-based frameworks (Scikit-learn, TensorFlow, PyTorch) Implement supervised and unsupervised learning techniques Optimize model performance and accuracy through iterative tuning Data Preparation & Integration Work with data engineers and integration teams to prepare, cleanse, and transform data Leverage data pipelines (e.g., IICS or ETL tools) to ensure reliable data availability Ensure data quality and consistency across systems AI Use Case Enablement Identify and define AI-driven opportunities aligned with GMU’s strategic goals Develop use cases such as: Student success and retention analytics Enrollment and demand forecasting Operational efficiency and automation Collaborate with stakeholders to translate business needs into analytical solutions Visualization & Reporting Develop dashboards and reports using Power BI/Tableau Present insights to business and academic stakeholders in a clear, actionable manner Model Deployment & Monitoring Support deployment of models into production environments Monitor model performance and ensure ongoing accuracy and relevance Work with DevOps teams for integration into enterprise systems Data Governance & Compliance Ensure adherence to data privacy and compliance standards (FERPA) Apply best practices for data security, masking, and ethical AI usage Required Qualifications 5+ years of experience in Data Science / Machine Learning Strong proficiency in Python (Pandas, NumPy, Scikit-learn, TensorFlow/PyTorch) Experience with data analysis, statistical modeling, and predictive analytics Experience working with large datasets and data pipelines Strong understanding of data visualization tools (Power BI, Tableau) Knowledge of SQL and relational databases Preferred Qualifications Experience in Higher Education environments, preferably with Banner data Familiarity with Informatica IICS or ETL tools Exposure to cloud platforms (Azure/AWS/GCP) Experience with NLP or advanced analytics use cases Understanding of MLOps practices and model lifecycle management Key Competencies Strong analytical and problem-solving skills Ability to translate complex data into actionable insights Effective communication with both technical and non-technical stakeholders Attention to data quality, accuracy, and governance Ability to work in a multi-project, collaborative environment Engagement Context Work within a Banner-centric integration ecosystem Collaborate with integration, data engineering, and business teams Support GMU in building a data-driven and AI-enabled decision framework Success Criteria Development of accurate and actionable predictive models Improved data-driven decision-making across GMU functions Alignment of AI use cases with institutional priorities High-quality, compliant, and well-governed data solutions Seamless integration of AI capabilities into GMU’s ecosystem This role enables GMU to transition toward a data-driven, AI-enabled institution, leveraging its Banner ecosystem and enterprise data assets effectively.