ZipRecruiter

Log In

2

Remote Civil Engineering Data Analyst Jobs in Baltimore, MD

T Rowe Price

Lead Data Engineer

Baltimore, MD · On-site +1

$113K - $136K/yr

Lead the design, development, and maintenance of Enterprise data platform and solutions, analytics ... Bachelor's or Master's degree in Computer Science, Engineering, Data Science, or related field (or ...

SG2 Recruiting

Data Engineer II

Baltimore, MD · Remote

$113K - $136K/yr

Remote first work environment * Collaborative, cross-functional technology team * Fast-paced ... Expand your expertise in cloud-based data engineering, healthcare analytics, and enterprise data ...

Under Armour

Sr. Data Analytics Engineer

Baltimore, MD · On-site +1

$125K - $165K/yr

Drive engineering best practices include testing, observability, modular modeling, and ... Location: Remote (East Coast strongly preferred to optimize collaboration with HQ and cross ...

Under Armour

Lead, Enterprise Data Analyst

Baltimore, MD · On-site +1

Work closely with project teams, enterprise developers, systems analysts, data scientists, and architects to deliver solutions aligned with the enterprise-wide data strategy. * Monitor changes in the ...

Varsity Tutors

PE - Civil - Structural Tutor

Laurel, MD · Remote

$30 - $40/hr

Deep knowledge of PE Civil Structural examination content covering structural analysis, steel design, concrete design, wood design, masonry, seismic design, and structural engineering codes including ...

previous pagenext page

Showing results 21-40

All JobsCivil Engineering Data Analyst JobsRemote Civil Engineering Data Analyst JobsRemote Civil Engineering Data Analyst Jobs in Baltimore, MD

Remote Civil Engineering Data Analyst information

See Baltimore, MD salary details

$33.8K

$82.1K

$135.1K

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

As of Aug 8, 2026, the average yearly pay for remote civil engineering data analyst in Baltimore, MD is $82,114.00, according to ZipRecruiter salary data. Most workers in this role earn between $62,100.00 and $96,400.00 per year, depending on experience, location, and employer.

How does a remote civil engineering data analyst collaborate effectively with on-site engineering teams?

As a Remote Civil Engineering Data Analyst, you’ll frequently interact with on-site engineers and project managers through digital collaboration tools. Effective communication is key—regular video meetings, shared project management platforms, and clear documentation help bridge the distance. You may also be responsible for translating complex data insights into actionable recommendations for field teams. Building strong virtual relationships and staying proactive in your communication ensures that your analyses directly support project goals and that any data-driven changes are smoothly implemented on-site.

What are the key skills and qualifications needed to thrive as a remote civil engineering data analyst?

To thrive as a Remote Civil Engineering Data Analyst, you need a solid background in civil engineering principles, data analysis, and a relevant degree such as a BS in Civil Engineering or Data Science. Familiarity with technical tools like AutoCAD, GIS software, SQL databases, and data visualization platforms is typically required. Strong problem-solving abilities, attention to detail, and effective communication are standout soft skills in this role. These competencies enable accurate analysis and interpretation of engineering data, supporting sound decision-making for remote project teams.

What is the difference between Remote Civil Engineering Data Analyst vs Remote Civil Engineering Technician?

AspectRemote Civil Engineering Data AnalystRemote Civil Engineering Technician
Required CredentialsBachelor's in Civil Engineering, Data Analysis or related field; proficiency in data toolsAssociate's or Bachelor's in Civil Engineering or related field; technical skills in surveying and construction
Work EnvironmentPrimarily remote, analyzing data, creating reports, supporting project decisionsRemote or on-site, assisting with surveys, inspections, and technical tasks
Employer & Industry UsageEngineering firms, consulting agencies, government agenciesConstruction companies, engineering firms, public works departments

The main difference is that Remote Civil Engineering Data Analysts focus on analyzing civil engineering data remotely to support projects, while Remote Civil Engineering Technicians handle technical field tasks and inspections, often requiring more hands-on work. Both roles may be remote but serve different functions within civil engineering projects.

What does a remote civil engineering data analyst do?

A Remote Civil Engineering Data Analyst is responsible for collecting, processing, and interpreting data related to civil engineering projects from a remote location. They work with data sets involving construction, infrastructure, transportation, and environmental systems to help engineers make data-driven decisions. Their tasks often include data visualization, statistical analysis, and reporting findings to project teams. By working remotely, they leverage digital tools and cloud-based platforms to collaborate and deliver insights efficiently.
What are popular job titles related to Remote Civil Engineering Data Analyst jobs in Baltimore, MD? For Remote Civil Engineering Data Analyst jobs in Baltimore, MD, the most frequently searched job titles are:
What job categories do people searching Remote Civil Engineering Data Analyst jobs in Baltimore, MD look for? The top searched job categories for Remote Civil Engineering Data Analyst jobs in Baltimore, MD are:
What cities near Baltimore, MD are hiring for Remote Civil Engineering Data Analyst jobs? Cities near Baltimore, MD with the most Remote Civil Engineering Data Analyst job openings:
Remote Civil Engineering Data Analyst jobs near you

Director, AI Engineering (Data Science)

Blend360

Columbia, MD • On-site, Remote

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Re-posted 18 days ago

Job description

Company Description
Blend is a premier AI services provider, committed to co-creating meaningful impact for its clients through the power of data science, AI, technology, and people. With a mission to fuel bold visions, Blend tackles significant challenges by seamlessly aligning human expertise with artificial intelligence. The company is dedicated to unlocking value and fostering innovation for its clients by harnessing world-class people and data-driven strategy. We believe that the power of people and AI can have a meaningful impact on your world, creating more fulfilling work and projects for our people and clients. For more information, visit www.blend360.com.
Job Description
We are seeking a visionary and execution-oriented Director of AI Engineering to join our team. In this senior, client facing role, you will own the full lifecycle of AI model development, setting technical strategy and ensuring that cutting-edge machine learning solutions move from concept to production with business impact at their core.
With roots in data science and hands-on expertise in custom transformer architecture, you will bring both the credibility to lead technical teams. You will operate at the intersection of stakeholder management and deep technical execution and you should be equally comfortable presenting to a senior audience and reviewing model architecture with your team.
This is a high-impact, high-autonomyy role with significant organizational influence. You will define the AI roadmap, establish engineering best practices, and champion a culture of rigorous, reproducible, and responsible machine learning.
Strategic Leadership & Team Management
  • Define technical investments with business objectives
  • Mentor, and manage AI/ML engineers, senior data scientists, and MLOps engineers-setting performance expectations and a high-performance culture.
  • Partner with cross-functional leaders to prioritize initiatives, allocate resources, and measure organizational impact.
  • Establish engineering standards, code review practices, and model governance frameworks across the AI org.

Custom Transformer Architecture & Model Development
  • Serve as the technical authority on deep learning architecture-personally leading the design and development of custom transformer models for sequence modeling, customer propensity scoring, audience segmentation, and churn prediction.
  • Drive innovation in attention mechanisms, positional encodings, and tokenization strategies specifically suited to tabular, time-series, and event-stream data common in marketing and telecom.
  • Oversee adaptation and fine-tuning of foundation models (BERT, T5, TabTransformer, LLMs) for proprietary client datasets, ensuring domain-specific performance.
  • Champion reproducible experimentation and architectural decision documentation across the team.

Data Science & Applied Analytics
  • Oversee end-to-end data science workflows: problem framing, feature engineering, model development, validation, and production deployment.
  • Ensure statistical rigor in experimental design, causal inference, A/B testing, and offline/online evaluation frameworks.
  • Guide the team in building robust data pipelines for large-scale structured and unstructured datasets, including clickstream, CRM, ad telemetry, CDRs, and network KPIs.

Client & Executive Engagement
  • Lead technical discovery and solutioning with enterprise clients translating ambiguous business problems into well-scoped AI initiatives.
  • Present AI strategy, model results, and roadmap updates to C-suite and senior client stakeholders with clarity and executive presence.
  • Contribute to business development: support RFP responses, lead technical portions of client proposals, and help grow the AI engineering practice.

MLOps, Infrastructure & Governance
  • Establish production standards for model deployment, monitoring, drift detection, and automated retraining across cloud platforms (AWS SageMaker, GCP Vertex AI, Azure ML).
  • Drive adoption of MLOps best practices including CI/CD for ML, containerization (Docker/Kubernetes), and experiment tracking (MLflow, W&B, DVC).
  • Implement model governance, explainability, and responsible AI standards in compliance with client and regulatory requirements.

Qualifications
  • Bachelor's or Master's degree in Computer Science, Statistics, Mathematics, or a closely related quantitative field; Ph.D. strongly preferred.
  • 10+ years of progressive experience in data science and machine learning, with at least 3-5 years in a people management or technical leadership role (Director, Sr. Manager, or Principal Engineer level).
  • Proven track record of leading high-performing AI/ML engineering teams in a fast-paced, client-facing or product environment.
  • Deep, hands-on expertise designing and training custom transformer architectures from scratch-not only fine-tuning pre-built checkpoints, but architecting novel attention mechanisms, embedding strategies, and model topologies.
  • Strong applied data science foundation: feature engineering, statistical modeling, causal inference, and experimental design across large-scale datasets.
  • Proficiency in Python and core ML/DL libraries: PyTorch (preferred), TensorFlow, HuggingFace Transformers, scikit-learn, XGBoost/LightGBM.
  • Direct experience with industry datasets in marketing & media (DSP/DMP logs, ad impression data, attribution pipelines, MMM) OR telecommunications (CDRs, network KPIs, subscriber behavior, churn datasets).
  • Command of SQL and large-scale data platforms: Spark, BigQuery, Snowflake, or Databricks.
  • Experience owning end-to-end MLOps: cloud deployment (SageMaker, Vertex AI, or Azure ML), monitoring, CI/CD for ML, and model governance.
  • Exceptional executive communication skills-able to translate complex model behavior into business language for C-suite and client audiences.

PREFERRED QUALIFICATIONS
  • Professional services experience across multiple client engagements or business units
  • Background in privacy-preserving ML: federated learning, differential privacy, or synthetic data generation-especially relevant in post-cookie marketing environments.
  • Knowledge of graph neural networks (GNNs) for social graph or network topology analysis in telecom contexts.
  • Published research or conference contributions (NeurIPS, ICML, KDD, RecSys, or industry equivalents) related to applied transformers, tabular deep learning, or domain-specific AI.
  • Experience with real-time inference and streaming ML pipelines (Kafka, Flink, or similar).
  • Demonstrated ability to build strategic partnerships with external clients, contributing to revenue growth or account expansion through technical leadership.
  • Deep experience with openai focused on embeddings
  • Experience building custom transformer models

Additional Information
The starting pay range for this role is $180,000 - $240,000. Actual compensation within the range will be dependent on several factors including but not limited to relevant experience, skills, certifications, training, and location. It is not typical for an individual to be hired at or near the top of the range and determining factors for compensation are considered for each individual circumstance. BLEND360 also offers a competitive benefits program to meet the health and financial well-being of our team and their families. You can look forward to a range of benefits including medical, dental, vision, 401K, PTO, paid holidays, commuter benefits, spending accounts, life insurance, disability coverage, and EAPs.

Apply