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Remote Data Science Civil Engineering Jobs (NOW HIRING)

Moody Engineering

Civil Engineer Designer

Columbus, OH · On-site +1

We offer flexible remote work and exceptional benefits! What You'll Do * Develop detailed plans and ... Education Bachelor of Science in Civil Engineering (BSCE) from an ABET-accredited institution. Why ...

V-CENTRIX-US LLC

GIS Tech Lead

Manhattan, NY · Remote

Computer Science * Civil Engineering * Geography * Remote Sensing * Related field Technical Skills ... GPS and survey data * CAD-GIS integration * ETL tools such as FME * DevOps and CI/CD pipelines ...

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$129.7K

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

As of May 30, 2026, the average yearly pay for remote data science civil engineering in the United States is $129,716.00, according to ZipRecruiter salary data. Most workers in this role earn between $114,500.00 and $137,500.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Remote Data Science Civil Engineer, and why are they important?

To thrive as a Remote Data Science Civil Engineer, you need a solid background in civil engineering principles, data analysis, and proficiency with programming languages like Python or R, often supported by an engineering degree and relevant certifications. Familiarity with software such as AutoCAD, GIS tools, data visualization platforms, and cloud-based collaboration systems is typically required. Strong problem-solving, communication, and self-motivation skills help you collaborate effectively across virtual teams and translate data insights into practical engineering solutions. These capabilities are essential for leveraging data to drive innovation and efficiency in civil engineering projects while working remotely.

How does a remote data science role in civil engineering typically interact with on-site engineering teams to ensure project alignment?

In a remote data science position within civil engineering, frequent collaboration with on-site engineering teams is essential to ensure data-driven insights align with practical project requirements. This is commonly achieved through regular video meetings, shared project management tools, and clear documentation of data methodologies and results. Remote data scientists often participate in cross-functional team discussions to translate complex analyses into actionable recommendations, bridging the gap between data insights and field implementation. Effective communication and proactive engagement are key to overcoming challenges posed by physical distance.

What is a remote data science civil engineering job?

A remote data science civil engineering job combines the principles of civil engineering with data science techniques, allowing professionals to analyze, model, and interpret complex engineering data from a remote location. These roles typically involve tasks such as data analysis, predictive modeling, simulation, and optimization to improve infrastructure design, construction, and maintenance. Professionals in this field use programming languages, statistical methods, and engineering software to solve real-world civil engineering problems, all while working outside of a traditional office environment.

Is data science dead in 10 years?

Data science in civil engineering and related fields is expected to evolve rather than become obsolete, as the demand for data-driven decision-making and modeling continues to grow. Skills in programming, statistical analysis, and machine learning will remain valuable, especially with increasing reliance on automation and smart infrastructure. Continuous learning and adaptation to new tools like Python, R, and data visualization platforms are essential for data scientists in this sector.

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

AspectRemote Data Science Civil EngineeringRemote Structural Engineering
Required CredentialsBachelor's or Master's in Data Science, Civil Engineering, or related fields; certifications in data analysis or civil engineeringBachelor's or Master's in Civil or Structural Engineering; PE license may be preferred
Work EnvironmentData analysis, modeling, and reporting using software like Python, R, or SQL; collaboration via online toolsDesign, analysis, and review of structural projects; remote collaboration with teams and clients
Employer & Industry UsageTech firms, consulting agencies, government agenciesConstruction firms, engineering consultancies, government agencies

Remote Data Science Civil Engineering focuses on data analysis and modeling within civil engineering projects, while Remote Structural Engineering emphasizes designing and analyzing structural components remotely. Both roles require engineering credentials but differ in daily tasks and software tools used.

More about Remote Data Science Civil Engineering jobs
What cities are hiring for Remote Data Science Civil Engineering jobs? Cities with the most Remote 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 Remote Data Science Civil Engineering jobs? States with the most job openings for Remote Data Science Civil Engineering jobs include:
What job categories do people searching Remote Data Science Civil Engineering jobs look for? The top searched job categories for Remote Data Science Civil Engineering jobs are:
Remote Data Science Civil Engineering jobs near you
Infographic showing various Remote Data Science Civil Engineering job openings in the United States as of May 2026, with employment types broken down into 64% Full Time, 18% Part Time, 6% Temporary, and 12% Contract. Highlights an 89% Physical, and 11% Remote job distribution, with an average salary of $129,716 per year, or $62.4 per hour.

Remote | Data Science & Analytics Workflow Consultant -- $75-$130/hour

24-MAG

New York, NY • Remote

$75 - $130/hr

Part-time

Posted 4 days ago

Job description

We are sharing a specialised part-time consulting opportunity for professionals experienced in data science, analytics engineering, business intelligence, SQL analysis, experimentation, data engineering, and structured data workflow review.

This role supports current and upcoming remote consulting opportunities focused on structured data science review, analytics workflow analysis, business intelligence assessment, experimentation review, data pipeline evaluation, metric documentation, and high-quality project execution. Selected professionals will apply their data and analytics expertise to review realistic technical scenarios, evaluate analytical requirements, prepare structured written outputs, and support accurate, evidence-based data workflow tasks.

Key Responsibilities

Professionals in this role may contribute to:

Analytics, BI & Metric Review

  • Review data scenarios involving SQL analysis, ad-hoc business questions, dashboard specifications, metric definitions, funnel analysis, cohort analysis, and reporting outputs
  • Evaluate analytical outputs against source data, defined business logic, expected numerical results, and documented requirements
  • Support structured review of SQL queries, BI dashboards, dashboard specs, metric documentation, and analytical summaries
  • Identify missing assumptions, query issues, metric inconsistencies, reporting gaps, and expected analysis outcomes

Experimentation & Data Science Support

  • Review experimentation scenarios involving A/B test design, readouts, lift calculations, statistical significance, guardrail metrics, and decision criteria
  • Evaluate experiment outputs against defined metrics, expected values, testing assumptions, and analytical standards
  • Support structured review of data science workflows, Python-based analyses, statistical outputs, and business interpretation materials
  • Prepare clear written explanations for data science and analytics decisions based on source materials and verifiable criteria

Data Engineering & Pipeline Workflow Review

  • Review data engineering scenarios involving ETL/ELT pipelines, dbt models, data quality monitoring, warehouse schema design, Airflow or Dagster DAGs, and pipeline documentation
  • Evaluate pipeline outputs, schemas, transformations, orchestration logic, and data quality checks against documented requirements
  • Support structured review of data artifacts such as dbt models, schema diagrams, data contracts, test suites, DAGs, and warehouse documentation
  • Maintain accuracy, consistency, and professional judgment across submitted work

Ideal Profile

Strong candidates may have:

  • 3+ years of experience as a data scientist, analytics engineer, BI analyst, data analyst, product analyst, data engineer, decision scientist, or related data professional
  • Working fluency in at least two areas such as advanced SQL, dbt, data warehousing, Snowflake, BigQuery, Redshift, experimentation, A/B testing, pipeline orchestration, metric modeling, or Python for analysis
  • Familiarity with tools such as SQL, Python, dbt, Airflow, Dagster, Snowflake, BigQuery, Redshift, Databricks, Looker, Tableau, Mode, Hex, Metabase, Power BI, or similar data and analytics systems
  • Comfort reading and preparing data artifacts such as SQL queries, dbt models, experiment readouts, dashboard specs, schema diagrams, metric definitions, and pipeline documentation
  • Strong written communication skills and ability to explain data decisions clearly
  • Ability to follow structured instructions and produce evidence-based work

Educational Background

  • A degree or professional background in data science, statistics, mathematics, computer science, economics, engineering, business analytics, information systems, or a related quantitative field is helpful
  • Equivalent practical experience in data science, analytics engineering, business intelligence, experimentation, data engineering, or data workflow review is also highly relevant

Nice to Have

  • Experience in product, consumer, SaaS, marketplace, fintech, e-commerce, or data-mature company environments
  • Familiarity with experimentation frameworks, metric governance, data quality monitoring, warehouse design, pipeline orchestration, or modern data stack workflows
  • Experience preparing or reviewing SQL queries, dbt models, experiment readouts, dashboards, schema diagrams, funnel analyses, cohort reports, or data documentation
  • Experience with Python-based analysis, statistical testing, data modeling, analytics engineering, or pipeline QA
  • Strong attention to detail in data-heavy, metric-heavy, and documentation-based technical environments

Why This Opportunity

  • Apply data science and analytics expertise to structured remote project work
  • Contribute to high-quality analytics review, experimentation assessment, BI documentation, and data pipeline workflow analysis
  • Work on flexible, project-based assignments aligned with your technical background
  • Use your data judgment in a focused, detail-oriented technical environment
  • Remote structure with competitive hourly compensation

Contract Details

  • Independent contractor role
  • Fully remote with flexible scheduling
  • Part-time commitment depending on project availability
  • Competitive rates between $75–$130 per hour depending on expertise
  • Weekly payments via Stripe or Wise
  • Projects may be extended, shortened, or adjusted depending on scope and performance
  • Work will not involve access to confidential or proprietary information from any employer, client, or institution

About the Platform

This opportunity is available through 24-MAG LLC. We connect experienced professionals with remote consulting opportunities across technical, evaluation, and project-based workstreams.

By submitting this application, you acknowledge that your information may be processed by 24-MAG LLC for recruitment and opportunity matching in accordance with our Privacy Policy: https://www.24-mag.com/privacy-policy.