Data Scientist

Summary

Provides full lifecycle qualitative and quantitative analysis and reporting for the “Con Ganas” Title V grant designed to improve WNMU’s institutional ability to better serve its Hispanic learners and communities. 

Duties

1. Acquires, manipulates, develops, and maintains longitudinal data sets, verifying accuracy and consistency over time, in the context of evolving requirements regarding institutional needs and the Title V Project. Provides relevant, timely, and accurate institutional information to university administrators.
2. Provides leadership, support, and management in all areas of data collection, data analysis, and data reporting relating to the goals, objectives, and activities associated with the “Con Ganas” Title V grant which include but not limited to student retention, attainment, levels of satisfaction, student support, instruction, learning, sense of belonging, self-efficacy, and community outreach.
3. Leads a cooperative effort with various university constituencies to optimize the quality, availability, and flows of relevant data and information throughout the university; provides leadership in the development and maintenance of accessible, user-friendly relational databases.
4. Collect and record quantitative and qualitative data from different digital and analog sources including the Banner CRM, Canvas LMS, survey data, focus groups, individuals, and events (counts, comments, feedback, discourse, frequencies).
5. Monitors quantitative and qualitative performance and quality control plans to identify improvements in institutional and departmental teaching, learning, learner support, outreach activities including dual enrollment and innovations designed to improve retention, attainment, sense of belonging, and self-efficacy.
6. Develops trainings, workshops, speaker series, and other events aimed at education and social sciences faculty and Title V stakeholders which include, but not limited, to AHSIE and HACU conference.
7. Assists with the development of technical support documentation for accessing quantitative data in existing and new enterprise platforms, e.g., Canvas LMS (Learning Management System), Banner CRM, related. Provides institution-wide support for obtaining data and information and performing analyses in response to specific needs.
8. Provides a broad range of administrative and supervisory functions. Supervises assigned staff in accordance with WNMU personnel practices including recruitment, training, performance evaluation, guidance, etc. Participates in the process of ongoing personal and professional development. Maintains comprehensive communication among all contacts (internal and external). Models professional standards and ethics in accordance with WNMU philosophy.
9. Performs other duties as assigned.

Education/Background

Master’s or terminal degree in data science, statistical analysis, learning science, learning analytics, or related field with 5 years of experience required. Doctorate degree with 7 years of experience preferred. Bilingual (Spanish) preferred. 

Job Knowledge

Experience applying various methods of numerical and categorical modelling techniques and supervised and unsupervised machine learning methods (OLS regression and GLMs, logistic regression, KNN, SVM, decision trees/random forest, clustering and cluster analysis, dimensionality reduction). Experience with survey tools including Qualtrics and SurveyMonkey. Experience conducting focus-group research sessions and synthesizing qualitative data using NVIVO or similar platform. Experience with IRB processes and procedures. Excellent communication skills including verbal, visual, and quantitative including data visualization tools such as Tableau, Plotly, and Zoho. Knowledge of statistic practices and procedures as well as related federal, state, and local laws and regulations. Must be knowledgeable of university policies, procedures, and regulations regarding data analysis functions. Must be able to handle multiple deadlines and maintain accuracy. Must be sensitive to cultural differences within the University and community. Fluent in Microsoft Office Applications. Knowledge of customer service principles, practices, and techniques. Must be able to effectively communicate information policies and/or procedures. Must be able of reviewing/analyzing a variety of reports and make recommendations. Experience with higher education, learning science, data analysis, reporting, data science, or some combination of these. 

Working Conditions/ Physical Demands (With or Without Accommodations)

Normal office environment. May travel some within the community when needed. May be required to lift normal office equipment and materials. Visual acuity to read information from computer screens, forms and other printed materials and information. Able to speak (enunciate) clearly in conversation and general communication. Hearing ability for verbal communication/ conversation/responses via telephone, telephone systems, and face-to-face interactions. Manual dexterity for typing, writing, standing, and reaching, flexibility, body movement for bending, crouching, walking, kneeling, and prolonged sitting. May be required to work additional hours or days depending on circumstances.