Senior Data Scientist

Description

Position Summary As a Senior Data Scientist, you will be responsible for designing and implementing machine learning models and data-driven solutions that enhance our water utility intelligence platform and create value for our customers. This position involves working with large-scale IoT data from millions of water meters, developing predictive analytics capabilities, and deploying AI solutions into production environments. You will collaborate with Product Management and Engineering teams to translate business requirements into data science solutions, mentor junior data scientists, and drive Neptune's AI transformation initiatives.

This role provides direct impact on utility operations, water conservation efforts, and customer service improvements.

• Effectively communicate and articulate decisions, designs, and outcomes to stakeholders at all levels of the organization.
• Work with cross-functional teams to deliver high-quality machine learning models and data science solutions.
• Understand and enhance requirements defined by Product Management for AI-powered features.
• Design and implement machine learning models for water consumption forecasting, anomaly detection, leak detection, and predictive maintenance.
• Develop and deploy production-ready machine learning pipelines on cloud infrastructure (AWS).
• Analyze large-scale time-series data from IoT devices and water utility operations.
• Build and optimize data processing workflows using PySpark and distributed computing frameworks.
• Create data visualizations and analytics dashboards to communicate insights to stakeholders.
• Conduct exploratory data analysis to identify patterns, trends, and opportunities in metering data.
• Perform feature engineering and model selection to optimize predictive performance.
• Evaluate model performance and implement monitoring solutions for production ML systems.
• Collaborate with software engineers to integrate ML models into the Neptune 360 platform.
• Provide technical guidance to Product Management on data science capabilities and feasibility.
• Document data science methodologies, model architectures, and analytical findings.
• Stay current with latest developments in machine learning, AI, and data science best practices.
• Mentor junior data scientists and disseminate technical knowledge within the organization.
• Review code and model implementations of other team members.
• Participate in sprint planning and demonstrate completed work at the end of every iteration.
• Work with Python, SQL, PySpark, AWS services (Sage Maker, Bedrock, Lambda, Redshift), and ML frameworks.
• Contribute to Neptune's AI strategy and identify new opportunities for data-driven innovation.

• 5+ years of experience in data science, machine learning, or related analytical roles.
• 5+ years of experience with Python and data science libraries (pandas, Num Py, scikit-learn, Tensor Flow/PyTorch).
• Strong experience with SQL and working with large-scale databases (Redshift, Postgre
  
  SQL, MySQL).
• Experience with PySpark and distributed computing frameworks for large-scale data processing, including working with common data formats such as JSON and Parquet.
• Proven track record of deploying machine learning models to production environments.
• Experience with cloud platforms, preferably AWS (Sage Maker, Bedrock, Lambda, S3, Redshift).
• Experience with time-series analysis and forecasting methods.
• Understanding of MLOps practices and model lifecycle management.
• Experience building RESTful APIs for model serving.
• Strong statistical analysis and experimental design skills.
• Experience with data visualization tools and techniques.
• Experience working in Agile/iterative development environments.
• Ability to communicate complex technical concepts to non-technical stakeholders.
• Experience with version control systems (Git) and CI/CD pipelines.
• Continued professional self-improvement through courses, certifications, or research.
• Preferred:
  Experience with AWS big data services (Glue, EMR, Athena).
• Preferred:
  Experience with IoT data, utility operations, or water management systems.
• Preferred:
  Experience with generative AI and large language models.

Master's or Ph.D. degree in Data Science, Computer Science, Statistics, Mathematics, or related quantitative field, or combination of Bachelor's degree with equivalent experience.

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