Job Description

The Utah Department of Transportation (UDOT) is seeking a forward-thinking, highly motivated individual with strong technical knowledge and communication skills to develop predictive analytics and performance measures to enhance the planning process and enable data-driven decision-making for the Traffic and Safety Division.

The overall vision is that the Highway Safety Predictive Modeling Specialist will enable new approaches to solving traffic and transportation problems to improve safety, system efficiency, and quality of life in our communities.

Key Responsibilities

The successful candidate will perform a variety of duties focused on data-driven safety improvements:

Develop and implement predictive models to forecast transportation safety risks and effective risk responses. Apply the methodologies and principles outlined in the Highway Safety Manual (HSM) to analyze crash data, identify high-risk locations, and evaluate the safety performance of designs and operational strategies. Evaluate existing and proposed Crash Modification Factors (CMF's) and appropriate Safety Performance Functions (SPF's) to improve safety evaluation tools. Integrate economic and safety analysis to prioritize safety improvements and transportation investments statewide. Utilize statistical software and programming languages (e.g., R, Python, SAS) to manage, analyze, and visualize large transportation datasets. Establish protocols for developing robust datasets through coordinated extraction and integration of multiple data sources. Collaborate with planners, engineers, data managers, and analysts to integrate predictive analytics and HSM insights into transportation plans and safety programs. Document processes and methodologies, and effectively convey concepts, key insights, and recommended actions to various stakeholders. Work with cloud-based technologies to ensure scalability, reliability, and security of data. Research, investigate, and recommend emerging technologies (e.g., AI/ML) to improve predictive analytics and highway safety research.

Minimum Qualifications

Education: Bachelor's degree or higher in Data Science, Economics, Econometrics, Statistics, Data Management, or another quantitative field OR equivalent experience Experience: At least three (3) year of professionally related experience. Technical Proficiency: Proficiency in statistical software packages such as R, Python, SAS, or similar. Experience with spatial data analysis and visualization.

Preferences

Preference may be given to those with expertise or experience in the following:

Google Workspace environment. Geospatial & Cloud: Familiarity with ESRI's ArcGIS software and solutions. Experience working with geospatial data and tools for mapping and analysis. Proven ability to connect ESRI solutions with Google Cloud Platform (GCP) services. Certification in GCP or relevant cloud technologies; experience leveraging GCP tools. Knowledge of containerization and orchestration tools (e.g., Docker, Kubernetes). UDOT or Highway Safety Manual datasets; knowledge of and experience with transportation and/or government.
Pay: $33.13 - $52.75 per hour

Benefits:

401(k) 401(k) matching Dental insurance Employee assistance program Employee discount Flexible spending account Health insurance Health savings account Life insurance Paid time off Parental leave Professional development assistance Retirement plan Tuition reimbursement Vision insurance
Work Location: In person