Data Analyst (Construction Management)

Gryps; United States; Remote; USD 70,000 - 90,000; Full time

Job summary

A data solutions firm is seeking an experienced Data Analyst to work within the construction industry. The successful candidate will leverage their expertise in quantitative data analysis and problem-solving to consult with customers, develop data-driven solutions, and utilize tools like SQL and Python. Strong familiarity with data visualization and construction-related software is a plus. This role promises opportunities for professional development and client interaction.

Qualifications

• 2+ years of experience in quantitative data analysis in construction.
• Experience working with customers and data-driven solutions.
• Ability to translate raw data into actionable insights.

Responsibilities

• Analyze data structures from construction systems.
• Set up customer dashboards and reconfigure business processes.
• Consult with customers to leverage data via Gryps.

Skills

Quantitative data analysis

Complex problem-solving

Proficiency in SQL

Proficiency in Python

Data visualization tools

Tools

Jupyter Notebook

e-Builder

P6

Procore

Autodesk

Job description

What we're looking for:

We need someone with 2+ years of experience in quantitative data analysis and complex problem-solving within the construction industry. You should be comfortable working directly with customers to identify data-driven solutions and have a track record of translating raw data into actionable insights. Proficiency in SQL and Python, along with experience using data visualization tools, is essential. Bonus points if you have familiarity with core owner systems like e-Builder, P6, Procore, or Autodesk, and a solid understanding of owner-side capital program data.

What you'll do:

• Analyze data structures from construction systems or public data sources.

• Set up customer dashboards, reconfigure business processes, or lead whiteboard sessions to map out customer data use.

• Consult with customers on how to leverage their data via the Gryps platform.

• Document data workflows, data policies, structures, standards, and procedures for customer systems.

• Develop and run advanced descriptive, predictive, and prescriptive analytics using Jupyter Notebook and Python.

• Act as both a data analyst and a customer success partner, diagnosing client needs and designing solutions.