What are the responsibilities and job description for the Data Scientist position at SOLTECH?
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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