Environmental Data Scientist – PFAS Chemistry Consulting

Job Description

Environmental Data Scientist | AECOM

The Tone:
This is a hybrid, full-time role at AECOM, located in Raleigh, NC. AECOM is a global infrastructure consulting firm, delivering a better world by improving commutes, keeping the lights on, providing clean water, and transforming skylines. This role is integral to supporting PFAS chemistry consulting services, building environmental AI/ML capabilities, and developing advanced analytical tools to solve complex challenges. The position contributes to impactful projects worldwide, helping communities thrive for future generations.

The TL;DR
• Role: Full Time
• Type: Hybrid – Raleigh, NC, USA
• Location: Hybrid – Raleigh, NC, USA
• Mission: To provide defensible scientific support for PFAS projects, advance environmental AI/ML capabilities, and ensure high-quality environmental data management for complex site investigations and remediation.
• Tech Stack: Python, SQL, Power BI, EQuIS, R, MATLAB, ArcGIS Pro, geopandas, Azure, Databricks, Snowflake, Git, MLOps, LLMs, NLP, EDD

What You’ll Actually Do
• Provide defensible scientific support for critical project decisions, especially related to PFAS source identification, apportionment, and conceptual site models.
• Design, develop, validate, and deploy machine learning, statistical, and generative AI applications tailored for environmental science and engineering problems.
• Build and maintain large-scale, curated libraries of environmental data, including analytical, geospatial, hydrogeologic, and unstructured document data, with standardized schemas and quality control.
• Develop and maintain extract, transform, and load (ETL) pipelines and relational databases to ensure the quality, integrity, and traceability of environmental data.
• Automate reporting deliverables, data validation, and data management workflows using programming languages and business intelligence tools.

The Must-Haves
• Background: Bachelor’s degree in Data Science, Statistics, Computer Science, Environmental Science or Engineering, Chemistry, Geology, or a related quantitative field, combined with 4+ years of relevant experience in environmental data analysis, data management, or environmental chemistry.
• Experience: 4+ years of relevant experience, with demonstrated ability to build, validate, and document statistical or machine learning models using real-world scientific or environmental datasets.
• Skills: Proficiency with Python (e.g., pandas, scikit-learn) and SQL for building ETL pipelines and managing relational databases; strong knowledge of environmental chemistry principles and analytical chemistry quality assurance/control.
• Bonus: Master’s degree in a quantitative, environmental, or chemistry-related discipline; experience applying multivariate statistical analyses or machine learning techniques to PFAS forensics; working knowledge of PFAS chemistry including analytical methods; experience with environmental data management systems like EQuIS or GIS and geospatial analysis tools; experience with cloud data platforms, version control, and MLOps practices; experience applying large language models and natural language processing.