Data Scientist - environmental engineering

Overview

Data Scientist - environmental engineering (remote allowed) — Data Scientist / Machine Learning Engineer position at Brown and Caldwell (BC) focused on designing, building, and deploying advanced analytics and machine learning models to solve environmental and water-related challenges.

Location:

Phoenix, AZ.

Employment type:

Full-time. On-site or remote work options available. Benefits include medical, dental, vision, life, retirement, and PTO.

• Collaborate with interdisciplinary teams to translate complex environmental problems into scalable data science and machine learning solutions.
• Design, train, and validate machine learning models using data from various sources.
• Lead the end-to-end ML lifecycle, from exploratory data analysis and feature engineering to model training, hyperparameter tuning, and deployment.
• Develop and implement MLOps practices to ensure models are scalable, reproducible, and monitored for performance drift in production environments.
• Apply advanced statistical methods and time-series analysis to support demand forecasting, anomaly detection in infrastructure, and predictive maintenance.
• Collaborate with Data Engineers to guide the design of data infrastructure.
• Stay up to date with emerging technologies, tools, and best practices in AI, Large Language Models (LLMs), and environmental engineering.

• Bachelor's in Computer Science, Data Science, Statistics, Applied Mathematics, Engineering, or a related field.
• Minimum of 5 years of experience in data science, machine learning engineering, or advanced analytics.
• Core Programming:
  High proficiency in Python (pandas, numpy, scikit-learn) and SQL.
• Big Data & Distributed Computing:
  Hands-on experience with PySpark and distributed training frameworks.
• Experience with Azure platform, Dev Sec Ops , and MLOps.
• Experience developing functional data processing workflows to transform raw data into reliable input for ML algorithms.
• Strong problem-solving skills and the ability to work in a collaborative, cross-functional environment.
• Excellent communication skills to interact with technical and non-technical stakeholders.
• A passion for staying updated with the latest trends, tools, and technologies.

• Master's degree in Computer Science, Data Science, Statistics, Applied Mathematics, Engineering, or a related field.
• 8+ years of experience in data science, machine learning engineering, or advanced analytics.
• Machine Learning & Statistics:
  Solid understanding of ML algorithms and statistical concepts. Experience with Deep Learning frameworks.
• MLOps & Engineering:
  Demonstrated knowledge of software engineering principles, version control (Git), and best practices for writing clean, production-ready code. Experience with CI/CD for ML.
• IoT & Time-Series:
  Experience with streaming data processing and time-series forecasting, particularly for IoT and edge compute applications.
• Geospatial:
  Knowledge of geospatial data processing and analysis (GIS, Geo Pandas).
• Demonstrated ability to engage with clients to identify needs.

The anticipated starting pay range for this position is based on the employee’s primary work location and may be more or less depending upon skills, experience, and education.

• Location A: $118,000 - $161,000
• Location B: $130,000 - $177,000
• Location C: $142,000 - $194,000

Comprehensive benefits package includes medical, dental, vision, and more.

Brown and Caldwell is a full-service environmental engineering and construction services firm.