Job Responsibilities

• Documents data and analytics needs in projects of medium/high complexity with a student and equity-centered lens, collaborating with peers, cross-functional partners, faculty staff, and leaders. Translates user stories into technical requirements.
• Sets and manages expectations about analytics tasks and activities through clear, timely, and effective communication with partners and stakeholders.
• Identifies adequate data sources and data sets to evaluate hypotheses and produce forecasts.
• Analyzes large data sets from both structured and unstructured sources and develops statistical and predictive models.
• Collaborates with Data Engineering in the development of ETL/ELT processes and data pipelines.
• Identifies, investigates, and solves complex data issues, contributing to the accuracy, completeness, consistency, timeliness, and validity of the university’s data.
• Utilizes software, scripts, and algorithms to perform complex data-related tasks (e.g., importing, cleaning, transforming, analyzing, displaying) without human intervention.
• Combines data analysis, visualization, and narrative structures to convey information in compelling ways that instigate deliberate action.
• Selects and deploys a variety of mathematical models, forecasting methods (e.g., time series, inferential, regression), descriptive statistics, and/or classification algorithms to make predictions and identify relationships based on limited sets of data.
• Conveys information effectively to peers, partners, and senior leaders, using a variety of resources and formats (synchronous and asynchronous, verbal and written) such as e-mails, presentations, meeting, and workshops.
• Creates and organizes information about processes, projects, operations, data assets, and insights from analyses, making it accessible in ways that increase the university’s knowledge and efficiency.
• Writes and interprets technical documentation (e.g. Entity-Relationship, Conceptual, Logical, and Physical data models).
• Contributes actively to the enrichment of the university’s data management platforms (e.g., data dictionaries, catalogs, etc.).
• Tracks and reports own progress, dependencies, and challenges diligently.
• Designs small-scale solutions and collaborates effectively with other technical specialists (e.g., data engineers) in the construction of data products, systems, and applications.
• Understands and abides by the relevant policies and methods to access, use, transform, store, and delete data in responsible, secure, and compliant ways.
• Works actively in improving own skills and knowledge through internal and external, formal and informal, structured and unstructured learning. Is a lifelong learner and embodies a growth mindset.