Senior Data Scientist
About The Position
Our client is seeking a Senior Data Scientist to lead the design and deployment of advanced machine learning solutions that power a next-generation water utility intelligence platform. This high-impact role focuses on transforming large-scale IoT data from millions of smart water meters into predictive insights that drive operational efficiency, water conservation, and enhanced customer service. The ideal candidate brings deep expertise in machine learning, cloud-based data platforms, and production-grade AI systems. You will partner closely with Product Management and Engineering to translate business objectives into scalable data science solutions while helping shape our client’s long-term AI strategy.
Requirements
- 5+ years of experience in data science, machine learning, or advanced analytics roles
- 5+ years of hands-on Python experience, including pandas, NumPy, scikit-learn, TensorFlow, and/or PyTorch
- Strong SQL expertise and experience working with large-scale databases (Redshift, PostgreSQL, MySQL)
- Experience with PySpark and distributed computing frameworks for large-scale data processing
- Proficiency working with common data formats such as JSON and Parquet
- Demonstrated success deploying machine learning models into production environments
- Experience with AWS cloud services, including SageMaker, Bedrock, Lambda, S3, and Redshift
- Expertise in time-series analysis and forecasting techniques
- Solid understanding of MLOps, model lifecycle management, and monitoring
- Experience building RESTful APIs for model serving
- Strong statistical analysis and experimental design capabilities
- Experience creating data visualizations and analytics dashboards
- Familiarity with Git, version control, and CI/CD pipelines
- Experience working in Agile development environments
- Ability to communicate complex technical concepts to non-technical audiences
- Commitment to continuous learning and professional development
Nice To Haves
- Experience with AWS big data services such as Glue, EMR, and Athena
- Background working with IoT data, utility operations, or water management systems
- Experience with generative AI and large language models (LLMs)
Responsibilities
- Communicate complex technical decisions, model designs, and analytical outcomes clearly to stakeholders across the organization
- Collaborate cross-functionally to deliver high-quality, scalable machine learning solutions
- Refine and enhance AI feature requirements in partnership with Product Management
- Design and implement models for: Water consumption forecasting Anomaly detection Leak detection Predictive maintenance
- Develop and deploy production-ready ML pipelines in AWS cloud environments
- Analyze and model large-scale time-series IoT data from water utility operations
- Build and optimize distributed data processing workflows using PySpark
- Perform exploratory data analysis (EDA) to uncover patterns, trends, and actionable insights
- Conduct feature engineering, model selection, and hyperparameter tuning to optimize predictive performance
- Evaluate, monitor, and maintain production ML systems using MLOps best practices
- Partner with software engineers to integrate ML models into a cloud-based utility platform
- Provide technical guidance on data science feasibility and AI capabilities
- Document methodologies, model architectures, and findings for knowledge sharing
- Stay current on advancements in machine learning, AI, generative AI, and data science innovation
- Mentor junior data scientists and conduct peer code and model reviews
- Participate in Agile sprint planning and iteration demos
- Contribute to enterprise AI strategy and identify new data-driven innovation opportunities
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What This Job Offers
Job Type
Full-time
Career Level
Senior
