Position Classification Description

Position Class Code / Title: L1022 / Data Scientist 1
Recruitment Tier: Tier 1
FLSA: Exempt
Grade: 14

This is a description of a Staff Position Classification. It is not an announcement of a position opening. To view descriptions of current openings, please go to UNMJobs and Search Postings to view positions that are currently accepting applications.

The following statements are intended to describe, in broad terms, the general functions and responsibility levels characteristic of positions assigned to this classification. They should not be viewed as an exhaustive list of the specific duties and prerequisites applicable to individual positions that have been so classified.


Utilizes advanced techniques to analyze data sets and to identify and predict trends and behavior analytics regarding activities of significant importance to the University; utilizes established and emerging techniques to find consistent patterns and correlations that help drive key performance indicators (KPIs). Develops, implements and maintains tools to extract and examine a wide variety of data from multiple internal, external, and/or non-traditional sources. Partners with stakeholders and subject-matter experts in various domains to operationalize analytical solutions that help decision makers at all levels of the institution gain necessary insights to improve institutional effectiveness and management.

Duties and Responsibilities

  1. Captures, mines, manages and analyzes big data sets using state-of-the-art techniques, such as natural language processing, cluster analysis, image analysis, pattern recognition, predictive modeling, visualization, and/or other applicable methods.
  2. Develops, tests, trains, and implements models; continuously refines models based on performance and outcome and operationalizes feasible solutions.
  3. Researches, examines and develops mathematical, statistical and/or machine learning models to predict outcomes, which may include the use of linear regression models, decision trees, random forest, and other applicable methods; models and frames scenarios that affect critical organizational processes and/or decisions.
  4. Collaborates with stakeholders and subject matter experts to understand institutional needs; identifies relevant data sources for information.
  5. Visualizes and reports data findings to stakeholders utilizing various visual formats; compiles and presents complex information for audiences at varying levels of technical understanding.
  6. Processes, cleanses, and verifies the integrity and reliability of data used for analysis; uses iterative processes and validates findings.
  7. Selects features for data mining, which may include building and optimizing classifiers using machine-learning techniques; explores, examines, and extracts data from multiple internal and external data sources to find hidden insights and correlations.
  8. Establishes and maintains appropriate data collection and storage systems, programs, and procedures for building analytic systems; ensures accurate and efficient data management.
  9. Champions the adoption of advanced analytics and data science across the entire institution and at operational, managerial and executive levels.
  10. Performs miscellaneous job-related duties as assigned.

Minimum Job Requirements

  • Bachelor's degree in a relevant field; at least 3 years of experience directly related to the duties and responsibilities specified.
  • Completed degree(s) from an accredited institution that are above the minimum education requirement may be substituted for experience on a year for year basis.

Knowledge, Skills and Abilities Required

  • Ability to analyze complex problems, interpret operational needs, and develop integrated, creative solutions.
  • Demonstrated analytical and problem-solving abilities, including skills in making recommendations and decisions.
  • Knowledge of current and emerging statistical, algorithmic, mining and visualization techniques.
  • Knowledge and appreciation of business concepts and requirements as applicable to a large academic, research, and/or health care facility.
  • Ability to learn and understand new concepts in order to develop solutions to institutional-level problems.
  • Ability to plan, create, program and manage complex statistical/predictive models.
  • Familiarity with basic principles of distributed computing and/or distributed databases.
  • Ability to apply statistical principles and processes to meet a range of information requirements.
  • Ability to communicate technical information to non-technical personnel.
  • Strong interpersonal and communication skills and the ability to work effectively with a wide range of constituencies in a diverse community.
  • Ability to format and generate summary, statistical, and presentation reports.
  • Ability to develop and deliver effective technical presentations, both verbally and in writing.
  • Knowledge of established programming procedures and programming languages.
  • Knowledge of current technological developments/trends in area of expertise.

Distinguishing Characteristics

    Position requires: a) Using independent judgment and relying on experience to perform tasks and problem solving of a complex nature; b) supporting and/or serving as project leader on sizeable projects; c) participating in the development, programming, and maintenance of complex databases; d) participating in the development of study design, methodology, and data analysis; and e)formatting data to develop and prepare reports, charts, tables, and other related documents.

Conditions of Employment

  • Employees who provide services or work in patient care or clinical areas are required to be in compliance with the University's influenza vaccination requirement.

Working Conditions and Physical Effort

  • No or very limited physical effort required.
  • No or very limited exposure to physical risk.
  • Work is normally performed in a typical interior/office work environment.

The University of New Mexico provides all training required by OSHA to ensure employee safety.

Revised Date: 08/08/2022