Reporting to the Director, Analytics Intelligence, 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. 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 initiate 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. May provide guidance to Data Scientist(s).
Essential Functions and 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.
- General Scope of Responsibilities: 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.
- Performs other duties as assigned.
Preferred Education, Certifications and Licensures
- Master's degree or higher in data science, statistics, economics, mathematics, engineering, or a related quantitative field is strongly preferred.
Required Education
- Bachelor's degree in data science, statistics, economics, mathematics, engineering, or a related quantitative field is required.
Required Experience and Skills
- 5+ year's experience in a data science or advanced analytics role.
- 3+ year's experience developing, deploying, and implementing predictive models.
- Superior 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.
- Proven experience investigating difficult problems with a natural curiosity in data discovery to create a high- quality solution.
- Demonstrated experience with hypothesis testing to ensure limitations and assumptions are either validated or minimized.
- Working knowledge of relational databases and database query tools (SQL Server or similar).
- Demonstrated experience with cloud environments including Azure, AWS, Google cloud, advanced analytic methods including machine learning techniques (Gradient Boosting, Random Forest, Neural Networks, Clustering, PCA, NLP, Image analytics, etc.
- Familiarity with model explanation methods including SHAP, PDP, LIME, Sabaas, etc.
- Experience creating data visualizations using Power BI, Tableau, or similar applications.
- Proficiency using R, Python, SAS, or similar languages.
- Strong Excel skills.
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