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Internship Data Science Civil Engineering Jobs in California

CYNET SYSTEMS

Principal Data Scientist

Oakland, CA · On-site

$128 - $148/hr

Master's Degree in Data Science, Machine Learning, Computer Science, Civil Engineering, Mechanical Engineering, Electrical Engineering, Statistics, or equivalent field. * Experience in Data Science ...

APTIM

Civil Engineering Intern

Concord, CA · On-site

$25 - $34.11/hr

Interns will be paired with experienced engineering and science staff who will provide training on ... Collaborate with current engineering staff in the interpretation of engineering data, conduct ...

APTIM

Civil Engineer Intern

Concord, CA · On-site

$25 - $29/hr

Interns will be paired with experienced engineering and science staff who will provide training on ... Collaborate with current engineering staff in the interpretation of engineering data, conduct ...

Tetra Tech

Site/Civil Engineering Intern

Oakland, CA · On-site

$20 - $26.25/hr

Why Tetra Tech At Tetra Tech, we are Leading with Science to solve the world's most complex ... Exposure to AutoCAD or Civil 3D through coursework or internships * Strong analytical ...

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Internship Data Science Civil Engineering information

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 are the most commonly searched types of Data Science Civil Engineering jobs in California?

The most popular types of Data Science Civil Engineering jobs in California are:

What are popular job titles related to Internship Data Science Civil Engineering jobs in California?

For Internship Data Science Civil Engineering jobs in California, the most frequently searched job titles are:

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

The top searched job categories for Internship Data Science Civil Engineering jobs in California are:

What cities in California are hiring for Internship Data Science Civil Engineering jobs?

Cities in California with the most Internship Data Science Civil Engineering job openings:

Internship Data Science Civil Engineering jobs near you

Principal Data Scientist

CYNET SYSTEMS

Oakland, CA • On-site

$128 - $148/hr

Contractor

Re-posted 13 days ago

Job description

Job Overview:

Pay Range: $128.66hr - $148.45hr

Requirement/Must Have:

  • Master’s Degree in Data Science, Machine Learning, Computer Science, Civil Engineering, Mechanical Engineering, Electrical Engineering, Statistics, or equivalent field.
  • Experience in Data Science, 8+ years or 2+ years experience if possessing Doctoral Degree or higher in a related field.

Responsibilities:

  • Researches and applies advanced knowledge of existing and emerging data science principles, theories, and techniques to inform business decisions.
  • Creates advanced data mining architectures/models/protocols, statistical reporting, and data analysis methodologies to identify trends in structured and unstructured data sets.
  • Extracts, transforms, and loads data from dissimilar sources for machine learning feature engineering.
  • Applies data science/machine learning/artificial intelligence methods to develop defensible and reproducible predictive or optimization models.
  • Wrangles and prepares data as input for machine learning model development and feature engineering.
  • Architects, develops, and documents reusable functions and modular code for data science.
  • Assesses business implications associated with modeling assumptions, inputs, methodologies, technical implementation, analytic procedures, and advanced data analysis.
  • Works with stakeholder departments and subject matter experts to understand application and potential of data science solutions.
  • Presents findings and makes recommendations to senior management.
  • Acts as peer reviewer of complex models.

Nice to Have:

  • Doctorate Degree in Data Science, Machine Learning, Computer Science, Civil Engineering, Mechanical Engineering, Electrical Engineering, Statistics, or equivalent field.
  • Expertise in experimental design and causal inference methods.
  • Expertise in statistical methods for time series analysis, statistical modeling, and probabilistic risk assessment.
  • Relevant industry experience (electric or gas utility, data science consulting, etc.).
  • Familiarity with the use of supervised, unsupervised, deep learning & physics-based methods for modeling electrical infrastructure failure modes.
  • Competency with data science standards and processes (model evaluation, optimization, feature engineering, etc.) along with best practices.
  • Knowledge of industry trends and current issues in job-related area of responsibility.
  • Competency with Agile product development best practices.
  • Proficiency with Python or PySpark, code reviews, and code development best practices.
  • Proficiency in explaining technical concepts including statistical inference, machine learning algorithms, software engineering, model deployment pipelines.
  • Mastery in clearly communicating complex technical details and insights to colleagues and stakeholders.
  • Ability to develop, coach, teach and/or mentor others to meet both their career goals and the organization goals.

Skills:

  • Pyspark proficiency.
  • User interface development proficiency.
  • Strong cross-functional collaboration skills.
 

Founded in 2010 and headquartered in the Washington, DC metro area, Cynet Systems Inc. is a leading staffing and recruiting powerhouse. Proudly recognized as a nationally and locally certified diversity firm, Cynet delivers agile, scalable talent solutions across industries. With an active footprint in all 50 U.S. states and Canada, we support thousands of consultants through our expansive, high-performing recruitment engine operating across North America and Asia—ensuring speed, quality, and consistency in every hire.
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About Cynet Systems

Sourced by ZipRecruiter

Cynet Systems Inc is a staffing and recruiting corporation nestled in Ashburn, VA, USA. Established in 2010, the company operates within the Information Technology and Services sector, specializing in providing effective workforce solutions to different business needs, including IT consulting, direct hire, and contract staffing services. Through the years, Cynet Systems has built an impressive portfolio, going beyond borders and expanding its operations internationally in Canada and India. Rooted in its core values of teamwork, leadership, and commitment, Cynet Systems helps businesses unlock their full potential by providing versatile and competent professionals that perfectly align with their needs. Fueled by their unwavering mission to deliver top-tier talent to businesses worldwide, Cynet Systems garnered various recognitions including SIA's fastest-growing staffing firms and Best Place to Work in Virginia for 2019.

Industry

It services

Company size

501 - 1,000 Employees

Headquarters location

Sterling, VA, US

Year founded

2010

Social media

Twitter

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