Role is onsite in Duluth, Georgia.

No third-parties will be considered.

Our client is seeking a Data Scientist to help power an innovative water utility intelligence platform. In this role, you’ll design and deploy machine learning models and advanced analytics solutions that transform large-scale IoT water meter data into actionable insights. You’ll work cross-functionally with product, engineering, and analytics teams to bring predictive models into production and drive measurable impact in water conservation, infrastructure optimization, and operational efficiency.

This is an exciting opportunity to expand your expertise in production-grade machine learning, cloud technologies, time-series analytics, and scalable data engineering while contributing to sustainability-focused technology initiatives.

What You’ll Do

Design, develop, deploy, and maintain machine learning models and scalable data science solutions
Partner with Product Management and Engineering teams to translate business requirements into analytical strategies and ML capabilities
Build predictive models for:
Water consumption forecasting
Leak detection
Anomaly detection
Predictive maintenance
Analyze large-scale, time-series IoT data from smart water meters and utility systems
Develop and optimize data pipelines using Python, SQL, and distributed computing frameworks
Perform exploratory data analysis (EDA) to identify trends, patterns, and operational insights
Conduct feature engineering, model experimentation, validation, and performance tuning
Create dashboards, visualizations, and reports to communicate insights to technical and non-technical stakeholders
Implement data quality checks, validation processes, and monitoring workflows
Collaborate with software engineers to integrate ML models into the Neptune 360 platform
Monitor and support production machine learning systems for reliability and performance
Document methodologies, codebases, and model development processes
Participate in code reviews and uphold software engineering and data science best practices
Work within cloud-based infrastructure environments, primarily AWS
Stay current on emerging ML techniques, tools, and industry trends
Participate in Agile sprint planning, standups, and iteration reviews
Support senior data scientists on advanced analytical initiatives
Continuously grow technical expertise through certifications, training, and hands-on learning

Required Qualifications

3+ years of experience in Data Science, Machine Learning, or a related analytical field
3+ years of hands-on Python experience using libraries such as pandas, NumPy, and scikit-learn
Strong SQL skills and experience working with relational databases
Proven experience building, evaluating, validating, and deploying machine learning models
Solid understanding of statistics, hypothesis testing, and experimental design
Experience with data visualization and storytelling best practices
Familiarity with cloud platforms such as AWS, Azure, or GCP
Experience using Git and version control workflows
Understanding of software development lifecycle (SDLC) and engineering best practices
Experience working in Agile or iterative development environments
Strong analytical thinking, problem-solving ability, and attention to detail
Excellent communication skills with the ability to explain technical concepts to diverse audiences
Demonstrated ability to learn new technologies quickly in a fast-paced environment

Preferred Qualifications

Experience with PySpark or distributed computing frameworks
Experience with time-series analysis and forecasting models
Hands-on experience with AWS services such as SageMaker, Lambda, S3, and Redshift
Experience with deep learning frameworks such as TensorFlow or PyTorch
Experience deploying machine learning models into production environments
Background working with IoT data, smart devices, or utility operations

Education

Bachelor’s or Master’s degree in Data Science, Computer Science, Statistics, Mathematics, Engineering, or a related quantitative field — or equivalent practical experience.

Why This Opportunity?

Work on cutting-edge IoT and machine learning solutions
Contribute to sustainability and water conservation initiatives
Gain hands-on experience with production ML systems and cloud technologies
Collaborate with high-performing cross-functional teams
Opportunity for growth, mentorship, and continued technical development

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