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Afternoon Data Science Civil Engineering Jobs (NOW HIRING)

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 ...

Blend360

Associate Director of Data Science

Columbia, MD · On-site

$58K - $59K/yr

Lead the delivery of AI and data science projects, managing a team of 4-5 developers and data ... Domain knowledge in civil engineering, manufacturing, structural engineering, or mechanical ...

Blend360

Associate Director of Data Science

Columbia, MD · On-site +1

$58K - $59K/yr

Lead the delivery of AI and data science projects, managing a team of 4-5 developers and data ... Domain knowledge in civil engineering, manufacturing, structural engineering, or mechanical ...

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Afternoon Data Science Civil Engineering information

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$51.5K

$147.5K

$197K

How much do afternoon data science civil engineering jobs pay per year?

As of Aug 19, 2026, the average yearly pay for afternoon data science civil engineering in the United States is $147,461.00, according to ZipRecruiter salary data. Most workers in this role earn between $84,000.00 and $196,000.00 per year, depending on experience, location, and employer.

What is the difference between Afternoon Data Science Civil Engineering vs Afternoon Data Science Structural Engineering?

AspectAfternoon Data Science Civil EngineeringAfternoon Data Science Structural Engineering
CredentialsDegree in Civil Engineering, Data Science certificationsDegree in Structural Engineering, Data Science certifications
Work EnvironmentConstruction sites, urban planning projectsDesign firms, building analysis environments
Industry UsageInfrastructure, transportation, urban developmentBuilding design, safety analysis, material testing

Both roles involve applying data science to engineering projects, but Civil Engineering focuses on infrastructure and urban projects, while Structural Engineering emphasizes building stability and safety. The required credentials and work environments overlap significantly, making them closely related but distinct specialties within engineering data science.

Can an afternoon data science civil engineer do data science?

An afternoon data science civil engineer can perform data science tasks if they have the necessary skills in data analysis, programming, and statistical methods. Their work schedule may influence project timing but does not limit their ability to apply data science techniques within civil engineering projects. Proficiency in tools like Python, R, or SQL is essential for effective data science work in this role.

What cities are hiring for Afternoon Data Science Civil Engineering jobs?

Cities with the most Afternoon Data Science Civil Engineering job openings:

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

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

What states have the most Afternoon Data Science Civil Engineering jobs?

States with the most job openings for Afternoon Data Science Civil Engineering jobs include:

Afternoon 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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