Data Scientist - environmental engineering

Data Scientist - environmental engineering

Job Category: Digital Consulting

Requisition Number: DATAS
007072

• Posted :
  September 25, 2026
• Full-Time
• Remote

Showing 1 location

Remote / Virtual

As a Data Scientist at Brown and Caldwell (BC), a leading environmental engineering firm, you will play a pivotal role in designing, building, and deploying advanced analytics and machine learning models that solve complex water and environmental challenges. We are using modern technology to transform the way that water is managed across the country.

This Data Science role assists cross-functional teams with identifying and defining opportunities to use AI and ML in the water and wastewater industry. The role develops and deploys models, generative and agentic AI solutions, web applications, and geospatial analyses to extract insights from diverse data sources under the supervision and guidance of more experienced data scientists. The role also supports cloud-based application development and deployment for internal and external users in collaboration with multidisciplinary project teams.

This role represents BC at conferences and in publications through technical presentations and papers. Work is performed under general supervision with limited autonomy.

This role is strategically important because it sits at the intersection of BC’s engineering expertise and the rapidly expanding digital future of the water industry. It brings advanced analytics, AI, machine learning, and real‑time decision support into a field where these capabilities are becoming essential for our clients. Your work will directly impact our ability to build digital solutions that ensure a future of clean water, thriving communities, and environmental protection.

In-person interviews may be required.

Responsibilities

• Conduct complex data analyses.
• Execute data science tasks such as exploratory data analysis, model building, statistical analysis, and feature extraction, and hyperparameter tuning.
• Set up data storage systems, preprocess data and create compelling data visualizations in standard platforms.
• Build and optimize machine learning models.
• Collaborate with cross-functional teams to understand data needs.
• Present findings to internal stakeholders and support client‑facing presentations.
• Follow best practices for software engineering and version control.
• Monitor and apply industry trends and research advancements in machine learning and applications in the water sector.
• Flexibility to adapt and execute various additional assignments based on evolving needs.
• May provide mentorship, guidance, support, and knowledge‑sharing to help less experienced team members develop their skills and grow within their roles.

Skills and Competencies

• Strong programming skills in languages such as Python and R, along with proficiency in relevant libraries and frameworks.
• Proficiency in writing clean, maintainable, and scalable code with minimal oversight.
• Strong communication skills and ability to present findings with some review and oversight.
• Basic knowledge of water/wastewater/environmental engineering and science topics.

Experience

• Typically, a minimum of 2 years of Data Science or related experience is required.
• Typically certified in the SMS Framework, and progressing through the SMS competencies.

Preferred Experience

• 4+ years of related work experience.
• Core Programming:
  High proficiency in Python (pandas, numpy, scikit-learn) and SQL.
• Experience developing and deploying generative AI applications, retrieval systems, and agentic workflows.
• Experience building data‑driven applications, APIs, web tools, and interactive user interfaces.
• Experience developing cloud‑based solutions and follow Dev Ops best practices for model and application deployment.
• Exp…