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ChatGPT Jobs · 22 hours ago

Data Scientist - environmental engineering

Phoenix, AZ

Full-time

Hybrid

Mid, Senior Level

$118K/yr - $194K/yr

5+ years exp

Brown and Caldwell is a full-service environmental engineering and construction services firm, and they are seeking a Data Scientist / Machine Learning Engineer to design, build, and deploy advanced analytics and machine learning models. The role involves collaborating with interdisciplinary teams to solve complex water and environmental challenges through scalable data science solutions.

Computer Software

Responsibilities

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 EDA 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

Qualification

PythonMachine LearningMLOpsSQLPySparkAzureDeep LearningGeospatialProblem-solvingCommunicationCollaboration

Required

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, DevSecOps, 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

Preferred

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, GeoPandas)

Demonstrated ability to engage with clients to identify needs