Senior Data Scientist

GHD•Pittsburgh, PA

1d•Hybrid

About The Position

EMPLOYER: GHD Services, Inc. JOB TITLE : Senior Data Scientist - Environmental Engineering LOCATION : 4068 Mt. Royal Blvd, Gamma Building, Suite 201, Allison Park, PA 15101 OPENINGS: 1 DUTIES: Develop, maintain, and optimize data pipelines for large-scale, complex datasets, and design and implement ETL processes to clean, transform, and structure raw environmental data. Design and build scalable and user-friendly applications using Microsoft Power Platform tools (Power BI, Power Apps, Power Automate). Develop custom workflows and integrations to streamline environmental engineering processes and improve operational efficiency. Analyze spatial data using GIS tools such as ArcGIS, QGIS, or Google Earth Engine for environmental and infrastructure projects. Create interactive maps, spatial visualizations, and predictive models for urban planning, resource management, and environmental impact analysis. Integrate geospatial data with machine learning and graph databases for advanced spatial modeling and decision-making. Ensure adherence to environmental compliance standards, including Environmental Protection Agency (EPA) regulations, Environmental, Social, and Governance (ESG) frameworks, and international sustainability guidelines. Conduct risk assessments for regulatory compliance in the oil and gas domain and other high-impact industries. Implement data-driven strategies for monitoring, reporting, and improving environmental metrics, including carbon emissions, water usage, and waste management. Develop tools and analytics to support audits and reporting for ESG initiatives and compliance with industry-specific standards. Design, train, and deploy machine learning models for predictive analytics, anomaly detection, and decision support systems in environmental engineering applications. Employ computer vision (CV) techniques for image analysis, such as remote sensing and urban planning. Utilize natural language processing (NLP) for analyzing textual data such as regulatory documents, reports, and research papers. Design and manage relational and non-relational databases for data storage and retrieval. Implement graph database solutions for spatial data modeling and network analysis in infrastructure planning. Use data-driven insights to support sustainable infrastructure development, environmental impact assessments, and resource optimization, and integrate environmental engineering principles into data science workflows to ensure regulatory compliance and ecological sustainability. Collaborate with cross-functional teams, including civil engineers, environmental scientists, and project managers, to identify opportunities for data-driven solutions. Develop long-term data science strategies aligned with the firm's objectives and client needs. Present technical findings and actionable insights to clients and senior management in a clear and concise manner and translate complex data science concepts into practical solutions for non-technical audiences. Oversee project timelines, budgets, and resources for data science, application development, and geospatial analytics initiatives, and ensure the successful delivery of high-quality analytical solutions and applications on time. Domestic (U.S.) travel required up to 10%. Telecommuting permitted up to 60%. REQUIREMENTS: Position requires a Master's degree in Data Science, Information Systems, Engineering or related field, and four (4) years of post-baccalaureate experience in job offered or in a Senior Data Scientist - Environmental Engineering - related occupation. Position requires experience in the following: Demonstrable proficiency in tools including Apache Spark and/or Hadoop, and cloud platforms such as AWS, Azure, and/or Google Cloud. Expertise in Microsoft Power Platform, including Power BI, Power Apps, and Power Automate, and ability to create low-code/no-code solutions for workflow automation and application design. Demonstrable proficiency in GIS tools such as ArcGIS, QGIS, or Google Earth Engine, understanding of geospatial data processing, spatial analysis techniques, and map creation, and experience integrating geospatial data with advanced machine learning and database technologies. Demonstrable familiarity with regulatory frameworks including EPA standards, ESG reporting guidelines, and environmental impact assessment methodologies, knowledge of compliance requirements for the oil and gas industry, including risk assessments, emissions tracking, and hazardous material monitoring, and proficiency in sustainability metrics, carbon accounting, and environmental auditing tools. Demonstrable experience in Computer Vision and related libraries such as OpenCV. Demonstrable understanding of supervised and unsupervised learning techniques and experience with frameworks such as TensorFlow, PyTorch, or Scikit-learn. Demonstrable expertise in NLP libraries SpaCy, Hugging Face, or NLTK for analyzing regulatory and legal documentation. Demonstrable knowledge of SQL, NoSQL (MongoDB, Cassandra), and graph databases (Neo4j and/or TigerGraph). Solid experience of full-stack web application development with modern frameworks such as React.js, Node.js, Vue, or Next.js. Demonstrable proficiency in Python, R, Java or C++, and experience with data visualization tools Tableau, Power BI, or Matplotlib. Demonstrable analytical and problem-solving skills with a solid understanding of fundamental principles in civil engineering or environmental science. Domestic (U.S.) travel required up to 10%. Telecommuting permitted up to 60%. CONTACT: Apply online at: LINK. EOE.

Requirements

Position requires a Master's degree in Data Science, Information Systems, Engineering or related field, and four (4) years of post-baccalaureate experience in job offered or in a Senior Data Scientist - Environmental Engineering - related occupation.
Position requires experience in the following: Demonstrable proficiency in tools including Apache Spark and/or Hadoop, and cloud platforms such as AWS, Azure, and/or Google Cloud.
Expertise in Microsoft Power Platform, including Power BI, Power Apps, and Power Automate, and ability to create low-code/no-code solutions for workflow automation and application design.
Demonstrable proficiency in GIS tools such as ArcGIS, QGIS, or Google Earth Engine, understanding of geospatial data processing, spatial analysis techniques, and map creation, and experience integrating geospatial data with advanced machine learning and database technologies.
Demonstrable familiarity with regulatory frameworks including EPA standards, ESG reporting guidelines, and environmental impact assessment methodologies, knowledge of compliance requirements for the oil and gas industry, including risk assessments, emissions tracking, and hazardous material monitoring, and proficiency in sustainability metrics, carbon accounting, and environmental auditing tools.
Demonstrable experience in Computer Vision and related libraries such as OpenCV.
Demonstrable understanding of supervised and unsupervised learning techniques and experience with frameworks such as TensorFlow, PyTorch, or Scikit-learn.
Demonstrable expertise in NLP libraries SpaCy, Hugging Face, or NLTK for analyzing regulatory and legal documentation.
Demonstrable knowledge of SQL, NoSQL (MongoDB, Cassandra), and graph databases (Neo4j and/or TigerGraph).
Solid experience of full-stack web application development with modern frameworks such as React.js, Node.js, Vue, or Next.js.
Demonstrable proficiency in Python, R, Java or C++, and experience with data visualization tools Tableau, Power BI, or Matplotlib.
Demonstrable analytical and problem-solving skills with a solid understanding of fundamental principles in civil engineering or environmental science.
Domestic (U.S.) travel required up to 10%.
Telecommuting permitted up to 60%.

Responsibilities

Develop, maintain, and optimize data pipelines for large-scale, complex datasets, and design and implement ETL processes to clean, transform, and structure raw environmental data.
Design and build scalable and user-friendly applications using Microsoft Power Platform tools (Power BI, Power Apps, Power Automate).
Develop custom workflows and integrations to streamline environmental engineering processes and improve operational efficiency.
Analyze spatial data using GIS tools such as ArcGIS, QGIS, or Google Earth Engine for environmental and infrastructure projects.
Create interactive maps, spatial visualizations, and predictive models for urban planning, resource management, and environmental impact analysis.
Integrate geospatial data with machine learning and graph databases for advanced spatial modeling and decision-making.
Ensure adherence to environmental compliance standards, including Environmental Protection Agency (EPA) regulations, Environmental, Social, and Governance (ESG) frameworks, and international sustainability guidelines.
Conduct risk assessments for regulatory compliance in the oil and gas domain and other high-impact industries.
Implement data-driven strategies for monitoring, reporting, and improving environmental metrics, including carbon emissions, water usage, and waste management.
Develop tools and analytics to support audits and reporting for ESG initiatives and compliance with industry-specific standards.
Design, train, and deploy machine learning models for predictive analytics, anomaly detection, and decision support systems in environmental engineering applications.
Employ computer vision (CV) techniques for image analysis, such as remote sensing and urban planning.
Utilize natural language processing (NLP) for analyzing textual data such as regulatory documents, reports, and research papers.
Design and manage relational and non-relational databases for data storage and retrieval.
Implement graph database solutions for spatial data modeling and network analysis in infrastructure planning.
Use data-driven insights to support sustainable infrastructure development, environmental impact assessments, and resource optimization, and integrate environmental engineering principles into data science workflows to ensure regulatory compliance and ecological sustainability.
Collaborate with cross-functional teams, including civil engineers, environmental scientists, and project managers, to identify opportunities for data-driven solutions.
Develop long-term data science strategies aligned with the firm's objectives and client needs.
Present technical findings and actionable insights to clients and senior management in a clear and concise manner and translate complex data science concepts into practical solutions for non-technical audiences.
Oversee project timelines, budgets, and resources for data science, application development, and geospatial analytics initiatives, and ensure the successful delivery of high-quality analytical solutions and applications on time.