Bachelors degree in Data Science, Engineering, Mathematics, or a related field.
Proven experience in data analysis, preferably in engineering or infrastructure sectors.
Strong proficiency in data analysis tools and programming languages (e.g., SQL, Excel, Python, R).
Knowledge of data visualization platforms (e.g., Power BI, Tableau) and statistical modeling techniques.
Strong problem-solving skills, attention to detail, and ability to communicate complex data findings clearly.
Responsibilities
Analyze and interpret large datasets related to civil engineering and environmental projects.
Support the development of reports, dashboards, and visualizations for stakeholders.
Collaborate with engineers and project managers to identify data needs and optimize workflows.
Ensure data integrity and accuracy through regular audits and validation processes.
Assist in regulatory compliance by maintaining organized datasets and adhering to standards.
Benefits
401(k)
401(k) matching
Health insurance
Dental insurance
Life insurance
Paid time off
Full Job Description
About the job Data Analyst
Note: Strictly for candidates with the Unites States only.
Key Responsibilities:
Analyze and interpret large datasets related to civil engineering, infrastructure, and environmental projects to drive insights and recommendations.
Support the development of reports, dashboards, and visualizations to communicate key metrics, trends, and project performance to stakeholders.
Collaborate with engineers and project managers to identify data needs, streamline workflows, and provide actionable insights for project optimization.
Ensure data integrity and accuracy through regular audits, data cleaning, and validation processes.
Assist in regulatory compliance efforts by maintaining organized datasets and ensuring adherence to industry standards and frameworks.
Qualifications:
Bachelors degree in Data Science, Engineering, Mathematics, or a related field.
Proven experience in data analysis, preferably in engineering or infrastructure sectors.
Strong proficiency in data analysis tools and programming languages (e.g., SQL, Excel, Python, R).
Knowledge of data visualization platforms (e.g., Power BI, Tableau) and statistical modeling techniques.
Strong problem-solving skills, attention to detail, and the ability to communicate complex data findings clearly.
