The Opportunity
The Data Scientist uses statistical techniques and database analysis tools to optimize business results and develop strategic insights. They work within the Institutional Research and Strategic Analytics team in the Information and Technology Solutions (ITS) department at Mines to teach data users and consumers how to work effectively with data. The position involves building a robust data culture, developing business intelligence reports, and supporting data governance and management. The Data Scientist also helps with external reporting obligations that adhere to state and federal policies.

Responsibilities
Data Strategy and Planning

Define data metrics, guidelines, and strategies with cross-departmental teams.
Create data mining and analytics architectures, data standards/definitions, statistical reporting, and data analysis methodologies.
Coordinate data resource requirements between teams.
Translate prototypes into production with stakeholders and team members.
Assist in developing data management policies and procedures.
Develop best practices for analytics composition and consumption.
Data Quality and Data Governance Management

Ensure usable and trustworthy data availability for business processes.
Analyze and improve data management components for better data quality.
Coordinate efforts between ITS teams and business units for data asset quality maintenance.
Investigate data quality issues, determine root cause and design corrective plans.
Develop and maintain operations of data management and governance system, including training for end users.
Lead development of data definitions, classification, standards, and quality with data stewards.
Develop monthly reports for the Data Governance Advisory Board on status of data definition development, data quality resolutions and issues preventing the delivery of data efficiently.
Conduct quality assurance checks on reports and data and develop tools for internal data audits.
Implement data literacy into daily conversations, coach data requestors, and increase data usage quality.
Acquisition and Deployment

Research and recommend data infrastructure, analytics tools, services, protocols, and standards.
Drive collection of new data and refine existing data sources.
Operational Management

Develop algorithms and predictive models to solve critical business problems.
Collaborate with academic and administrative units for data-informed decision-making.
Create tools and libraries for efficient interface with large datasets.
Analyze large datasets and identify meaningful patterns for actionable results.
Develop and automate enhanced imputation algorithms.
Create informative data visualizations.
Provide and apply quality assurance best practices for data science services.
Develop, implement, and maintain change control and testing processes.
Collaborate with administrators to ensure effective protection and integrity of data assets.
Plan, implement, and evaluate surveys.
Develop annual reporting on peer comparisons, trends, opportunities, and concerns in higher education.
Extract data from business intelligence tools and build dashboards and written reports.
Support compliance and accreditation data collection efforts.
External Reporting

Develop consistent, longitudinal, and reproducible data sources that support fulfilling external commitments required for compliance or are otherwise critical to the institution’s mission.
Serve as an institutional representative with external organizations (e.g. IPEDS, HLC, U.S. News, etc.) and formally submit required/requested data by their respective deadlines.
Minimum Qualifications
Bachelor’s degree in Statistics, Applied Mathematics, Computer Science, Engineering, or related discipline. Individuals without a related degree may be considered if they demonstrate possession of the same knowledge level found in a degree but have attained advanced knowledge through a combination of work experience and intellectual instruction.
2+ years of relevant work experience in a technical field.
Experience working in data visualization software.
Proficiency in SQL, Python, and/or R programming.
Understanding of statistical analysis, predictive modeling, and data engineering techniques.
Expertise in analyzing complex, large-scale, and multidimensional data from various sources.
Strong problem-solving skills with a quantitative approach and experience in statistical analysis.
Knowledge of data collection, cleaning, and transformation techniques.
Passionate about empirical research and data-driven decision-making.
Flexible in analytical approach, able to provide results with varying levels of precision.
Excellent reporting, data visualization, and technical writing skills.
Effective prioritization and execution of tasks in high-pressure environments.
Detail-oriented and experienced in project management.
Excellent written, verbal, and presentation communication skills.
Quality assurance and troubleshooting proficiency.
Proactive in fostering collaboration with internal and external stakeholders.
Preferred Qualifications
Master’s degree with strong math and analysis skills.
Experience with state and federal higher education policies.
Experience with surveying and rankings for higher education.
Experience with ERP systems (ex: Banner, PeopleSoft, Workday).
Experience implementing or utilizing a data warehouse.
An understanding of the organization’s goals and objectives.
Knowledge of applicable data privacy practices and laws.
Understanding of data warehousing and ETL techniques.