Senior Data Scientist (Onsite)

Summary

Reporting to the Executive Director Analytics and Reporting, the Senior Data Scientist provides analytical guidance and support to organizational decision makers via analysis, interpretation, and modeling of data. Leverages critical thinking and problem-solving skills to extract valuable business insights. Supports the entire analytics lifecycle including requirements gathering, problem formulation, solution design, analytical modeling, and presenting findings. Develops algorithms to extract and leverage insights from data to optimize organizational opportunities. Supports the deployment and implementation of analytical solutions with constant performance monitoring. Utilizes AI to development solutions more efficiently and explore previously inaccessible data.

Possesses a passion for applying data and analytics while consistently developing personal and organizational capabilities. Aids the organization to consistently be more data-driven and seek actionable insights. Tells a story with data by finding relationships, drawing conclusions, and making recommendations. Develops predictive models and prescriptive solutions to help maximize student success for all students. Possesses an innate ability to apply a champion-challenger approach throughout the analytics lifecycle. Mines complex data to create statistical models, reports/visualizations, machine learning models, and identify champion predictive models for deployment. This role is expected to leverage AI-enabled and agentic coding tools to enhance analytical productivity, accelerate development, improve model evaluation, and support high-quality, well-documented analytical solutions. May provide guidance to Data Scientist(s).

Essential Functions & Responsibilities

• Design and write programs and algorithms to train, test and develop complex analysis, predictive models, and detailed insights using Python, R, SPSS Modeler, SAS, and other appropriate best practice tools. Perform ad hoc requests to provide supervised and unsupervised analysis on student academic and success data, recruitment and enrollment data, state board pre-licensure exams, financial and operational data, and other efforts as assigned.
• Analyzes enterprise-wide data to understand behaviors and trends. Applies iterative process of analyze, test, learn, pivot or scale approach to analytical solutions. Develops and maintains predictive models to support prescriptive solutions including machine-learning algorithms. Applies both supervised and unsupervised methods to discover hidden insights within data.
• Interprets data using statistical techniques to analyze results and present output. Presents information using data visualization techniques and software. Distills complex data sets into a narrative that optimizes organizational outcomes while applying the art of storytelling. Proposes solutions and strategies to solve business opportunities. Monitors deployed solutions to ensure degradation and issues are proactively identified.
• Query, extract and mine necessary large data from Oracle CVUE database, CRM, IR&A Data Warehouse, College Board, IPEDS, National Student Clearing House, Common Dataset, and other utilities and sources. Be a champion of rigorous data integrity and collection across the institution.
• Utilizes AI-assisted and agentic development tools (e.g., Claude Code or similar solutions) to improve data evaluation, code development, model testing, and documentation while maintaining rigorous standards for accuracy, governance, and security.
• Collaborates with key stakeholders.
• Adheres to University policies and procedures and conducts job responsibilities in accordance with the standards set out in the University’s Code of Ethical Conduct, Compliance Agreement, Sexual Harassment Policy or any of its policies and procedures, applicable federal and state laws, and applicable professional standards.
• Maintains regular and timely attendance, reports to work as scheduled and assures time worked and/or time-off is recorded properly.
• Maintains confidentiality of all student, associate, and/or University information as required.
• Exercises care, proper use and maintenance of department equipment and supplies and identifies unsafe conditions and makes appropriate adjustments.
• Maintains order, cleanliness, and safety at work.
• Performs other duties as assigned.

Minimum and Preferred Qualifications

• Bachelor’s degree in data science, statistics, economics, mathematics, engineering, or a related quantitative field required.
• Master’s degree or higher in data science, statistics, economics, mathematics, engineering, or a related quantitative field strongly preferred.

Experience & Skills

• 3+ year’s experience developing, deploying, and implementing predictive models required.
• 5+ year’s experience in a data science or advanced analytics role preferred.
• Experience and working knowledge of model design, data analysis, exploratory quantitative methods feature/variable creation, model development, analytical solution implementation, and explainable advanced analytics methods.
• Demonstrated experience with hypothesis testing to ensure limitations and assumptions are either validated or minimized.
• Demonstrated experience and working knowledge of relational databases and database query tools (SQL Server or similar).
• Demonstrated experience and working knowledge of LLM.
• Demonstrated ability to leverage AI-assisted and agentic coding tools to improve technical workflows, including code development, debugging, testing, documentation, and model evaluation.
• Ability to critically assess, validate, and refine AI-generated code and analytical outputs to ensure statistical rigor, reproducibility, security, and alignment with organizational standards.
• Demonstrated experience with cloud environments including Azure, AWS, Google cloud, etc.
• Demonstrated experience with advanced analytic methods including machine learning techniques such Gradient Boosting, Random Forest, Neural Networks, Clustering, PCA, NLP, etc.
• Experience creating data visualizations using Power BI, Tableau, or similar applications.
• Proficiency using Python, or similar languages.
• Ability to use excellent organizational and analytical skills to self-direct, self-pace, multi-task, and function well under pressure of deadlines and conflicting priorities.
• Ability to gather data from multiple resources and synthesize information for analysis purposes.
• Ability to translate business needs into actionable requirements for developing appropriate solutions.
• Ability to simplify complexity for non-analytical and non-technical audiences.
• Ability to prioritize and perform multiple tasks simultaneously.
• Ability to effectively communicate, written and orally.
• Strong Excel skills.

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