Data Scientist - environmental engineering (remote allowed)

As a Data Scientist / Machine Learning Engineer 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. Your work will directly impact our ability to build digital solutions that ensure a future of clean water, thriving communities, and environmental protection.

The Data Scientist 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.

This position:

• Modernizes BC's service offerings.
• Supports our engineers across all practices.
• Improves quality and speed of deliverables.
• Helps build a forward-looking technical culture.
• Enhances our ability to generate and deliver digital value to clients.

The ideal candidate will have:

• Data science + ML depth.
• Background in water, civil, or environmental engineering (or interest /willingness to learn the industry).
• Fresh ideas on how to refine/rethink methods on how BC delivers analytics.
• Aptitude to "sell" digital/AI solutions and communicate value to clients.

Remote work is allowed within the U.S.

Responsibilities

• Collaborate with interdisciplinary teams of environmental engineers, data engineers, and software developers to translate complex environmental problems into scalable data science and machine learning solutions.
• Design, train, and validate machine learning models (supervised, unsupervised, and deep learning) using data from various sources, including high-frequency IoT sensor data, historical records, and geospatial information.
• Lead the end-to-end ML lifecycle, from exploratory data analysis (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, ensuring that datasets are optimized for analytical modeling and machine learning workloads.
• Stay up to date with emerging technologies, tools, and best practices in AI, Large Language Models (LLMs), and environmental engineering to drive continuous improvement.

Required Qualifications

• 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 in a professional setting.
• 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, specifically:
  
  
  
  • Azure Machine Learning Studio (managing experiments, model registry, endpoints).
  • Azure Databricks and Azure Synapse Analytics.
  • Azure Cognitive Services / OpenAI API integration.
  
  
  
  
• 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, with the ability to explain complex model outputs to engineering leaders.
• A passion for staying updated with the latest trends, tools, and technologies in data science and environmental engineering.

Preferred Qualifications

• 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 in a professional setting.
• Machine Learning & Statistics: Solid understanding of ML algorithms (Regression, Clustering, Random Forests, Gradient Boosting, Neural Networks) and statistical concepts. Experience with Deep Learning frameworks (TensorFlow, PyTorch).
• 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 (e.g., GitHub Actions, Azure DevOps).
• 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 and effectively sell or position data-driven consulting solutions, including translating technical capabilities into clear business value.

Salary Range: 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. These ranges may be modified in the future.

Location A: $118,000 - $161,000

Location B: $130,000 - $177,000

Location C: $142,000 - $194,000

You can view which BC location applies to you here. If you have any questions, please speak with your Recruiter.

Benefits and Other Compensation: We provide a comprehensive benefits package that promotes employee health, performance, and success which includes medical, dental, vision, short and long-term disability, life insurance, an employee assistance program, paid time off and parental leave, paid holidays, 401(k) retirement savings plan with employer match, performance-based bonus eligibility, employee referral bonuses, tuition reimbursement, pet insurance and long-term care insurance. Click here to see our full list of benefits.

About Brown and Caldwell

Headquartered in Walnut Creek, California, Brown and Caldwell is a full-service environmental engineering and construction services firm with 50 offices and over 2,100 professionals across North America and the Pacific. For more than 75 years, we have created leading-edge environmental solutions for municipalities, private industry, and government agencies. We strive to be the company of choice-to our clients, who benefit from our passion for delivering exceptional quality, and to our employees, present and future, who share our commitment to client service, collaboration, and innovation. Join us, and you will find a home where you can do your best work, reach new levels of expertise, and enjoy exceptional development opportunities. For more information, visit www.brownandcaldwell.com

This position is subject to a pre-employment background check and a pre-employment drug test.

Notice to Third Party Agencies: Brown and Caldwell does not accept unsolicited resumes from recruiters or employment agencies. In the event a recruiter or agency submits a resume or candidate without a previously signed agreement and approved engagement request with Brown and Caldwell, Brown and Caldwell reserves the right to pursue and hire those candidate(s) without any financial obligation to the recruiter or agency.

Brown and Caldwell is proud to be an EEO/AAP Employer. Brown and Caldwell encourages protected veterans, individuals with disabilities, and applicants from all backgrounds to apply. Brown and Caldwell ensures nondiscrimination in all programs and activities in accordance with Title VI of the Civil Rights Act.