Data Analyst II: Structures & Hydraulics for State Infrastructure

State of Vermont; Barre Town (VT); On-site; USD 65,000 - 90,000; Full time

Benefits offered by this job

Health benefits

Dental plan

Paid holidays

Leave plan

FMLI

Pension plan

Deferred compensation 457(b)

Tuition reimbursement

Flexible spending accounts

Life insurance

Wellness program

Student loan forgiveness

Job summary

State of Vermont, Agency of Transportation, seeks a Data Analyst to join the Structures & Hydraulics Project Delivery team. The role focuses on delivering accurate cost estimates and creating decision-ready dashboards by integrating diverse data sources.

The candidate will apply statistical analysis, R/Python, and machine learning to support statewide investments while collaborating with engineers and specialists in construction cost estimating.

Qualifications

• Bachelor's degree or higher in engineering, statistics, data science, GIS, CS, or closely related field.
• OR Associates degree in engineering, statistics, data science, GIS, CS, or closely related field AND two or more years of relevant work experience.
• OR High school diploma or equivalent with four or more years of work experience in related areas such as statistics, data science, geospatial analysis, or program management.

Responsibilities

• Integrate hydrologic, environmental, and pavement condition data into decision-ready dashboards.
• Support staff and subject matter experts by ensuring project estimates are accurate and reflect trends.
• Collaborate with engineering and cost-estimating teams to inform statewide investments.

Skills

Data analysis

Power BI

Excel

R/Python

Machine learning

Education

Bachelor's degree or higher

Associate degree with 2+ years experience

High school diploma with 4+ years experience

Job description

State of Vermont, Agency of Transportation, seeks a Data Analyst to join the Structures & Hydraulics Project Delivery team. The role focuses on delivering accurate cost estimates and creating decision-ready dashboards by integrating diverse data sources.

The candidate will apply statistical analysis, R/Python, and machine learning to support statewide investments while collaborating with engineers and specialists in construction cost estimating.