Mass Appraisal Analyst

Tulsa County

1d•$5,000•Onsite

About The Position

Performs data analysis, modeling, and reporting to support informed decision-making. Applies statistical, machine learning, and analytical methods to large datasets, develops predictive and prescriptive models, and communicates insights to stakeholders. This position may be filled at an entry, advanced, or senior level depending on education, experience, and demonstrated technical competence. This position is intended to be more than an addition to staff, it is designed to function as a force multiplier. This job description may be updated at any time to accommodate evolving requirements and responsibilities of the Assessor’s Office. All Job Descriptions are approved as final by the HR Director for the Tulsa County Assessor as of the listed revision date above. Reasonable accommodations may be made to enable individuals with disabilities to perform essential functions of the position. All offers for employment are contingent upon a positive background check. All Assessor Employees are expected to: • Work independently and in a team with tact, support, and cooperation for customers, co-workers, and supervisors. • Be capable of effectively using Microsoft suite of office software to include Word and Excel. • Perform other duties as assigned, assist in all functions of the office, and train co-workers. • And be aware that work may be occasionally required outside normal business hours, and time off may be discouraged during certain customer-support periods. As this is a public office, and due to conflict of interest concerns, all employees of the Tulsa County Assessor’s Office must place any real estate license in an INACTIVE status while employed here, or as soon as any current transactions are completed. Job Description Performs data analysis, modeling, and reporting to support informed decision-making. Applies statistical, machine learning, and analytical methods to large datasets, develops predictive and prescriptive models, and communicates insights to stakeholders. This position may be filled at an entry, advanced, or senior level depending on education, experience, and demonstrated technical competence. This position is intended to be more than an addition to staff, it is designed to function as a force multiplier. Examples of Work Performed Collects, cleans, validates, and maintains structured and unstructured datasets. Designs, develops, and deploys predictive and statistical models, including regression, classification, clustering, and time-series models. Performs exploratory data analysis to identify trends, anomalies, and relationships. Prepares dashboards, visualizations, and reports for management and departmental staff. Works collaboratively to support evidence-based policy, resource allocation, and operational improvements. Conducts ad hoc analyses to address business questions or support decision-making. Documents methodologies, model assumptions, limitations, and findings. Mentors Residential AND Commercial staff, and shares best practices for coding, statistical methods, and reproducible workflows. Participates in professional development, including workshops, courses, and certifications relevant to data science. Automates recurring analyses to improve efficiency and scalability. NOTE During first year of employment, incumbent will work in the role of a Residential Appraisal Sales Analyst/Modeler, to learn the needs of appraisal, and mass appraisal modeling.

Requirements

Knowledge of probability, statistical analysis, machine learning, and data modeling techniques, including regression, classification, clustering, and time-series methods.
Ability to extract, clean, and manipulate large datasets from multiple sources.
Proficiency with commonly used analytical programming languages (Python, R, SQL) and data visualization tools (Tableau, Power BI, or equivalent).
Ability to interpret and communicate technical results to non-technical stakeholders.
Ability to work independently or collaboratively depending on assignment level.
Bachelor’s degree in Data Science, Statistics, Mathematics, Computer Science, Information Systems, or a closely related field; and/or An equivalent combination of education, training, and successful experience sufficient to perform duties of the position.
Advanced and senior levels require progressively responsible experience in statistical modeling, data analysis, or applied analytics.
Ability to apply mathematical and statistical concepts, including percentages, ratios, measures of central tendency and dispersion, probability, and regression modeling.
Ability to perform, interpret, and apply results of statistical and machine learning analyses in practical and operational contexts.
Ability to read and analyze procedures, and government regulations.
Ability to write reports, business correspondence, and procedures.
Ability to effectively present information with clarity, and clearly respond to questions from groups, managers, coworkers, and taxpayers.
Strong problem-solving and critical thinking skills.
Ability to define analytical problems, collect and organize relevant data, establish valid conclusions, and implement solutions.
Ability to interpret complex technical instructions, handle multiple variables, and adapt methods to structured and unstructured data in a public-sector environment.

Responsibilities

Collects, cleans, validates, and maintains structured and unstructured datasets.
Designs, develops, and deploys predictive and statistical models, including regression, classification, clustering, and time-series models.
Performs exploratory data analysis to identify trends, anomalies, and relationships.
Prepares dashboards, visualizations, and reports for management and departmental staff.
Works collaboratively to support evidence-based policy, resource allocation, and operational improvements.
Conducts ad hoc analyses to address business questions or support decision-making.
Documents methodologies, model assumptions, limitations, and findings.
Mentors Residential AND Commercial staff, and shares best practices for coding, statistical methods, and reproducible workflows.
Participates in professional development, including workshops, courses, and certifications relevant to data science.
Automates recurring analyses to improve efficiency and scalability.