Data Analyst Intern

Hoffman Construction Company; Claude (TX); On-site; USD 35,000 - 43,000; Part time

Job summary

Hoffman Construction Company is seeking a Data Analyst Intern to help extract insights from diverse data sources, develop reporting tools (Excel, Smartsheet, Power BI), clean data, and ensure data quality and privacy. You will prepare construction data for data science initiatives and build dashboards in Power BI.

You will collaborate with project teams, mine historical data, and assist on data science workflows, while committing to ~20 hours per week during the school year.

Qualifications

• High School diploma or GED required.
• Pursuing a bachelor’s degree in Data Science, Mathematics, Statistics, CS, Engineering, or equivalent.
• Construction methods knowledge preferred.

Responsibilities

• Extract, transform, and load data for analysis and reporting.
• Check data quality and clean data when needed.
• Maintain reports and dashboards for Department and Project Managers.
• Create Power BI reports and dashboards.
• Assist data analyst on construction projects with duties as assigned.
• Mine historical construction data and improve quality.
• Support data strategy with data flowcharts and swim lanes.
• Assist in data science efforts and machine learning workflows.
• Host meetings to teach the Data team something new.
• Publish meeting minutes and follow up on actions.
• Complete DataCamp/Enterprise DNA/LinkedIn Learning courses.

Skills

Data analysis

Time management

Team player

Communication skills

Attention to detail

Problem solving

Education

High School diploma or GED

Bachelor's degree in Data Science, Mathematics, Statistics, Computer Science, Engineering

Tools

Power BI

Python

Smartsheet

Procore

Excel

Word

Outlook

PowerPoint

Teams

Matplotlib

Seaborn

Job description

Description

The Data Analyst Intern will help to drive informed decision-making by extracting insights from diverse data sources. The intern may assist the project team or departments by developing and maintaining reporting and analytical tools (Excel, Smartsheet, Power BI), cleaning data and ensuring data quality, ensuring data privacy and security, data visualization and reporting, and other duties as assigned. The Data Analyst Intern will also help prepare construction data for data science initiatives. The work commitment during the school year is roughly 20 hours per week. You will work with your team to come up with a work schedule that will allow you to achieve 20 hours per week of work time during your school year.

Salary Range:

$25.13 - $31.50 per hour (plus assignment adjustment, if applicable)

PRINCIPAL RESPONSIBILITIES:

• Extract, transform, and load data from diverse data sources for data analysis and reporting uses.
• Check for data quality and clean data, if necessary.
• Help to maintain reports and dashboards for Department Managers and Project Managers.
• Create reports and dashboards in Power BI.
• Assist the data analyst on a construction project with duties as assigned.
• Help to mine historical construction data and improve data quality where needed.
• Assist in data strategy efforts, including updating data flowcharts and creating data swim lanes.
• Assist in data science efforts such as identifying current construction activities where machine learning or Python automation might be useful, sourcing data for data science activities, preparing data for data science activities, training, and testing machine learning algorithms, and building data science workflows.
• Host a meeting with the objective of teaching the Data team something new.
• Write and publish meeting minutes. Follow up on meeting action items.
• Complete data course(s) in DataCamp, Enterprise DNA, and/or LinkedIn Learning.

QUALIFICATIONS:

Position Related Skills

• Experience in Windows and Microsoft Office 365 (Excel, Word, Outlook, Power Point and Teams), and have a general understanding of working within a computer network.
• Knowledge of, or ability to quickly learn, project management software such as Procore or Smartsheet.
• Experience with data analysis tools such as MS Power BI and Python.
• Experience with data reporting tools such as MS Power BI, Matplotlib, and Seaborn.
• Knowledge of, or experience with, Python programming and machine learning algorithms.
• Be willing to travel for up to a week to a project site that may be located outside of the Pacific Northwest.
• Demonstrate an understanding of construction and/or a willingness to learn in a fast-paced, on the job environment.
• Highly developed visual observation and interpretation skills.
• Ability to work well and maintain a cooperative attitude through high-pressure situations.
• Excellent time-management skills and ability to multi-task and prioritize work while frequently interrupted by phone calls and questions on work in progress.
• Excellent written and oral communication skills with an ability to develop strong interpersonal relationships.
• Ability to work closely with a variety of trade and craft people in a field work situation. Patience and professionalism are essential.
• Must be a strong team player with the ability to collaborate with various personnel within and across departments and at all levels of leadership.

Professional Experience and Education:

• High School diploma or GED required.
• Pursuing a bachelor’s degree in Data Science, Mathematics, Statistics, Computer Science, Engineering, or equivalent degree and/or equivalent field work experience preferred.
• Education background or experience in methods of construction preferred.

Physical and Mental Requirements:

• Workday is a combination of being stationary and moving about the work location. Must be able to spend equal amounts of time in a stationary position in an office environment and moving about the construction site.
• Must be able to ascend and descend ladders, scaffolds, and stairs.
• Constantly operates a computer and other office productivity machinery, such as a calculator, copy machine, and computer printer.
• Specific vision abilities required include close vision, depth perception and the ability to adjust focus in an outdoor environment. The worker is required to have close vis