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Manager 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 ... Presents findings and makes recommendations to senior management. * Acts as peer reviewer of ...

McGough Construction

Manager, Data Science

Raleigh, NC · On-site

MANAGER, DATA SCIENCE The Manager of Data Science will build and lead a focused, high-impact team ... Strong programming experience in Python (or equivalent), including data manipulation, modeling, and ...

CarGurus

Manager, Data Science

Boston, MA

Role overview The Manager, Data Science will lead an Inventory & Dealer Data Science team focused ... The Manager partners with Product, Engineering, Analytics, and cross-functional stakeholders to ...

LexisNexis

Manager Data Science

Raleigh, NC · On-site +1

$115K - $192K/yr

... As a Manager, Data Science, you will be a subject matter expert, defining projects and their ... You will work closely with other data scientists and engineers to design, develop, and deploy ...

RELX

Manager Data Science

Raleigh, NC · On-site +1

$115K - $192K/yr

... As a Manager, Data Science, you will be a subject matter expert, defining projects and their ... You will work closely with other data scientists and engineers to design, develop, and deploy ...

Paylocity

Manager Data Science

Schaumburg, IL · On-site

Manager Data Science Position Overview The Paylocity Data Science team is focused on building ... DevOps, etc.) or GCP (BigQuery, Compute Engine. etc.) • Familiar with cloud-based source code ...

Capital One

Manager, Data Science

Mclean, VA · On-site +1

Exercising discretion at a more senior level, partner with a cross-functional team of data scientists, software engineers, and product managers to deliver a product customers love. Leverage a broad ...

Paylocity

Manager Data Science

Manager Data Science Position Overview The Paylocity Data Science team is focused on building ... DevOps, etc.) or GCP (BigQuery, Compute Engine. etc.) • Familiar with cloud-based source code ...

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Manager Data Science Civil Engineering information

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

As of Jul 11, 2026, the average yearly pay for manager data science civil engineering in the United States is $97,145.00, according to ZipRecruiter salary data. Most workers in this role earn between $66,000.00 and $125,500.00 per year, depending on experience, location, and employer.

Can you make $500,000 as a civil engineer?

A Manager in Data Science within civil engineering can potentially earn $500,000 annually, especially with extensive experience, advanced skills, and leadership roles overseeing large projects or teams. Such high salaries are typically found in senior management positions, consulting, or firms working on large-scale infrastructure projects, often requiring specialized certifications and a strong track record. Entry-level or mid-career civil engineers generally earn significantly less than this amount.

What engineers make $300,000 a year?

Senior data science managers and experienced civil engineering managers can earn $300,000 or more annually, especially with extensive experience, advanced skills, and leadership responsibilities. High salaries are often associated with roles in large organizations, specialized expertise, or positions requiring advanced certifications and management of complex projects.

What is the difference between Manager Data Science Civil Engineering vs Civil Engineering Project Manager?

AspectManager Data Science Civil EngineeringCivil Engineering Project Manager
Required CredentialsMaster's in Data Science, Civil Engineering, or related field; certifications in project management or data analyticsBachelor's or Master's in Civil Engineering; Professional Engineer (PE) license often preferred
Work EnvironmentData analysis teams, engineering firms, research institutionsConstruction sites, engineering firms, project offices
Employer & Industry UsageTech-driven civil engineering projects, infrastructure analyticsConstruction projects, infrastructure development, urban planning

The Manager Data Science Civil Engineering focuses on analyzing data to optimize civil engineering projects, while the Civil Engineering Project Manager oversees the planning, execution, and completion of civil construction projects. Both roles require engineering knowledge but differ in their core responsibilities and work environments.

What engineers make $500,000?

Senior data science managers and specialized civil engineering roles with extensive experience and advanced skills can reach salaries of $500,000 or more, especially in high-demand industries or senior leadership positions. Achieving this level often requires advanced degrees, certifications, and a strong track record of project success and leadership. Compensation varies based on location, company size, and individual expertise.

Can a civil engineer become a data scientist?

A civil engineer can become a data scientist by acquiring skills in programming, statistics, and machine learning, often through additional education or training. Their background in engineering and problem-solving can be advantageous, but they typically need to learn data analysis tools like Python, R, and SQL, and gain experience with data modeling and visualization.
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Manager Data Science Civil Engineering jobs near you
Principal Data Scientist

Principal Data Scientist

SPECTRAFORCE TECHNOLOGIES Inc.

Oakland, CA • On-site

Other

Posted 4 days ago

Job description

Principal Data Scientist
12 months+ contract
Oakland, CA-Hybrid (one day per week onsite)
****Local Candidates Only****
Equipment: Client'' laptop will be provided upon start (or within a few days). If delayed, personal device may be used via Citrix/VDI
Top Skills:

  • Pyspark Proficiency
  • User Interface Development Proficiency
  • Strong Cross-Functional Collaboration Skills

Qualifications
Minimum:

  • 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 possess Doctoral Degree or higher in Data Science, Machine Learning, Computer Science, Civil Engineering, Mechanical Engineering, Electrical Engineering, Statistics, or equivalent field.

Desired:

  • 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 to implement them
  • Knowledge of industry trends and current issues in job-related area of responsibility as demonstrated through peer reviewed journal publications, conference presentations, open source contributions or similar activities
  • Competency with Agile product development best practices.
  • Proficiency with Python or Pyspark, code reviews, and code development best practices.
  • Proficiency in explaining in breadth and depth technical concepts including but not limited to 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

Position Summary:
Leads the design, development, and execution of scripts, programs, models, user interfaces, algorithms, and processes, using structured and unstructured data from disparate sources and sizes, generating for defensible, valid, scalable, reproducible and documented machine learning and artificial intelligence models (predictive or optimization) for problem solving and strategy development. Educates the non-technical community on advantages, risks, and maturity levels of data science solutions.
Job 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 from across client for their machine learning feature engineering
  • Applies data science/ machine learning /artificial intelligence methods to develop defensible and reproducible predictive or optimization models that involve multiple facets and iterations in algorithm development.
  • Wrangles and prepares data as input of 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 processes, and advanced data analysis.
  • Works with stakeholder departments and company subject matter experts to understand application and potential of data science solutions that create value.
  • Presents findings and makes recommendations to senior management.
  • Act as peer reviewer of complex models.

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