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.