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Internship Data Science Civil Engineering Jobs in Wheaton, IL

Numerator

Director, Data Science

Chicago, IL · On-site

As Director of Data Science , you will lead the team responsible for Numerator's consumer panel ... You'll partner closely with Market Science, Engineering, Product, and GTM to turn that signal into ...

Varsity Tutors

FE - Civil Engineering Tutor

Chicago, IL · Remote

$18 - $40/hr

What We Look For In a FE - Civil Engineering Tutor * Advanced Test Mastery: Deep knowledge of FE ... science to create personalized learning experiences. Through 1-on-1 Online Tutoring, students ...

Varsity Tutors

FE - Civil Engineering Tutor

Oak Lawn, IL · Remote

$18 - $40/hr

What We Look For In a FE - Civil Engineering Tutor * Advanced Test Mastery: Deep knowledge of FE ... science to create personalized learning experiences. Through 1-on-1 Online Tutoring, students ...

Varsity Tutors

FE - Civil Engineering Tutor

Wheaton, IL · Remote

$18 - $40/hr

What We Look For In a FE - Civil Engineering Tutor * Advanced Test Mastery: Deep knowledge of FE ... science to create personalized learning experiences. Through 1-on-1 Online Tutoring, students ...

Burns & McDonnell

Civil Engineering Intern (Chicago)

Chicago, IL · On-site

$18 - $23.50/hr

Our Engineering Interns are responsible for performing tasks requiring the application of standard ... Participate in continuous improvement efforts by collecting and analyzing data. * Present solutions ...

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Internship Data Science Civil Engineering information

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How much do internship data science civil engineering jobs pay per hour?

As of Sep 5, 2026, the average hourly pay for internship data science civil engineering in Wheaton, IL is $19.19, according to ZipRecruiter salary data. Most workers in this role earn between $16.25 and $21.15 per hour, depending on experience, location, and employer.

What is an internship data science civil engineering role?

Internship data science roles in civil engineering involve using data analysis, machine learning, and statistical methods to solve problems in areas like construction, transportation, and infrastructure. Interns may work with large datasets from sensors, surveys, or simulations to help civil engineers make better decisions about design, safety, and efficiency. These roles often require knowledge of programming languages like Python or R, as well as an understanding of civil engineering principles. Interns gain practical experience by working on real-world projects, often supporting tasks such as predictive modeling, data visualization, and report generation.

What skills and qualifications are needed for an internship data science civil engineering?

To thrive as an intern in Data Science for Civil Engineering, you need a foundational understanding of civil engineering principles, basic statistics, and data analysis, often supported by ongoing or completed coursework in civil engineering or data science. Familiarity with programming languages like Python or R, knowledge of data visualization tools, and experience with software such as MATLAB or AutoCAD are typically required. Strong analytical thinking, attention to detail, and effective communication skills help interns interpret data and present findings clearly. These skills are essential for leveraging data-driven insights to solve engineering challenges and support project decision-making.

What types of projects can I expect to work on during an internship data science civil engineering?

As a Data Science intern in Civil Engineering, you may be involved in projects such as analyzing structural health monitoring data, optimizing transportation systems using predictive modeling, or automating data collection from construction sites. Interns often collaborate with engineers and data professionals to interpret large datasets, develop machine learning models, and create visualizations that support infrastructure planning and decision-making. The work environment is typically interdisciplinary, giving you valuable exposure to both technical data science tools and practical civil engineering applications.

What is the difference between Internship Data Science Civil Engineering vs Civil Engineering Intern?

AspectInternship Data Science Civil EngineeringCivil Engineering Intern
Required CredentialsBasic knowledge of data science, programming, civil engineering fundamentalsEnrolled in civil engineering degree, basic engineering coursework
Work EnvironmentData analysis, modeling, software tools, field visitsSite visits, design work, construction supervision
Employer & Industry UsageEngineering firms, government agencies, construction companiesConstruction firms, consulting agencies, government departments
Common Search & ComparisonInternship Data Science Civil EngineeringCivil Engineering Intern

The Internship Data Science Civil Engineering focuses on applying data analysis and modeling within civil engineering projects, often involving software tools and data-driven decision making. In contrast, a Civil Engineering Intern typically engages in site visits, design tasks, and construction supervision. Both roles serve as entry points into the civil engineering industry but emphasize different skill sets and work environments.

What job categories do people searching Internship Data Science Civil Engineering jobs in Wheaton, IL look for?

The top searched job categories for Internship Data Science Civil Engineering jobs in Wheaton, IL are:

What cities near Wheaton, IL are hiring for Internship Data Science Civil Engineering jobs?

Cities near Wheaton, IL with the most Internship Data Science Civil Engineering job openings:

Internship Data Science Civil Engineering jobs near you
Infographic showing various Internship Data Science Civil Engineering job openings in Wheaton, IL as of August 2026, with employment types broken down into 1% As Needed, 84% Full Time, 11% Part Time, and 4% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $39,906 per year, or $19.2 per hour.

Director, Data Science

Numerator

Chicago, IL • On-site

Full-time

Re-posted 27 days ago

Job description

At Numerator, understanding consumers begins with one of the industry's richest and most comprehensive views of real-world purchasing behavior. For more than a decade, Numerator has pioneered and led the science of representing consumer purchasing behavior across retailers, channels, brands, categories, demographics, and geographies.
As Director of Data Science, you will lead the team responsible for Numerator's consumer panel - the quality, currency, and representativeness of the signal at the heart of our data. Your team owns how well the panel reflects the population, how we understand where it doesn't, and the methodologies that keep it accurate, current, and trustworthy. You'll partner closely with Market Science, Engineering, Product, and GTM to turn that signal into products and estimates clients rely on.
We're looking for a leader who enjoys challenging assumptions, translating client needs into innovation, and developing exceptional data scientists. You should be equally comfortable debating statistical methodology, mentoring a team, partnering with Engineering and Product, and explaining complex concepts in language that drives better business decisions.
What You'll Do:
Team Leadership:
  • Lead, coach, and develop a team of data scientists and data science managers focused on consumer behavior, panel methodology, and measurement science
  • Grow the leaders on your team - developing managers, not only individual contributors - and raise the technical bar through mentorship, methodology reviews, and adoption of modern statistical approaches
  • Foster a culture of scientific curiosity, rigor, and peer review, where decisions are grounded in evidence and healthy debate rather than precedent or intuition
  • Build an AI-native data science team by thoughtfully integrating AI into research, experimentation, software development, and scientific workflows - helping scientists move faster while maintaining rigorous standards
  • Maintain regular engagement with clients to deepen understanding of their challenges, build confidence in Numerator's methodology, and keep client needs central to the team's priorities

Consumer Science & Methodology
  • Own the quality, currency, and representativeness of the panel signal end to end - advancing methods for attribution completeness, compliance, anomaly detection, and keeping panelist demographics current
  • Characterize how the panel represents - and mis-represents - the population, treating that as a first-class, proactive modeling discipline rather than reactive data cleanup
  • Steward the panel as a living asset, partnering across the business on recruitment, engagement, and panel health, and turning evidence of where the panel is thin into targeted, prioritized investment
  • Design methodologies that improve the stability, consistency, explainability, and scientific defensibility of Numerator's consumer data

Statistical Innovation
  • Challenge existing approaches through first-principles thinking, and research, prototype, and productionize new statistical and machine learning methods where they strengthen the platform
  • Partner with Market Science to advance the statistical foundations of Numerator's products

Cross-Functional Leadership
  • Partner closely with Market Science, Engineering, Product, and GTM - contributing the deep panel understanding that powers the broader measurement system, and translating scientific advances into scalable product capabilities
  • Communicate complex technical concepts clearly to technical and non-technical audiences
  • Balance scientific rigor with practical business impact and client value

Skills & Requirements
  • 8+ years applying advanced statistical modeling to large, complex, real-world datasets
  • Experience leading data science teams, including developing managers or leading through other leaders
  • Deep expertise in statistical modeling, machine learning, and probabilistic reasoning
  • Strong grounding in panel, survey, or sampling methodology - weighting, representativeness, and measurement science
  • Experience working with noisy observational data and developing methods to improve data quality, representativeness, or inference
  • Experience developing production methodologies rather than exploratory analyses, and designing statistical systems rather than simply applying existing techniques
  • Strong programming skills in Python, with working knowledge of SQL
  • Excellent communication skills, with the ability to explain complex statistical concepts to diverse audiences, including external/client audiences

You'll stand out if you have:
  • Experience with Bayesian statistics, hierarchical modeling, probabilistic inference, or state-space models
  • Experience with causal inference, experimental design, or behavioral modeling
  • Experience developing statistical methods for consumer, retail, marketing, or longitudinal datasets
  • A demonstrated ability to challenge existing methodologies and introduce new scientific approaches into production
  • A systems-thinking approach that considers how improvements in one area influence the broader measurement platform

There is strength in numbers - We are the Numerati
Numerator is 2,000 employees strong. We have the confidence to be real and embrace what makes each Numerati unique. Our diverse experiences, ideas and backgrounds fuel our innovation.
Being part of the Numerati means that we'll take care of you! From our Recharge Days, maximum flexibility policy, wellness resources for employees and their families, development opportunities and much more - we're always finding ways to better support, celebrate and accelerate our team.

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