Water Analytics Data Scientist

Talentify; Duluth (GA); On-site; USD 90,000 - 140,000; Full time

Job summary

Talentify in Duluth, GA is seeking a Data Scientist to develop and deploy ML models for water utility data. You will work with IoT time-series data, design predictive maintenance, anomaly detection, and forecasting models, and collaborate with cross-functional teams to bring analytics into production.

Ideal candidates have 3+ years in data science, strong Python/SQL skills, and experience with cloud platforms and DS tooling.

Qualifications

• 3+ years of experience in data science, ML or related analytical roles.

Responsibilities

• Collaborate to develop and deploy machine learning models and data science solutions.
• Translate requirements with Product Management into analytical approaches.
• Build models for forecasting, anomaly detection, leak detection, and predictive maintenance.
• Analyze time-series IoT data from water utilities.
• Develop data processing workflows using Python, SQL, and distributed computing frameworks.
• Perform exploratory data analysis to identify patterns and insights.
• Implement data quality checks and validation procedures for pipelines.
• Collaborate with engineers to integrate ML models into Neptune 360 platform.
• Monitor model performance and contribute to production ML systems.
• Document methodologies, code, and model implementations.
• Participate in code reviews and follow DS best practices.
• Stay current with ML developments and feed back to roadmap.
• Work with cloud-based data infrastructure and ML tools (AWS preferred).

Skills

Python

Pandas

NumPy

scikit-learn

SQL

Data visualization

Git

AWS

Azure/GCP

Agile

PySpark

Education

Bachelor's or Master's in Data Science/CS/Statistics

Tools

Git

AWS SageMaker

TensorFlow/PyTorch

Job description

Talentify in Duluth, GA is seeking a Data Scientist to develop and deploy ML models for water utility data. You will work with IoT time-series data, design predictive maintenance, anomaly detection, and forecasting models, and collaborate with cross-functional teams to bring analytics into production.

Ideal candidates have 3+ years in data science, strong Python/SQL skills, and experience with cloud platforms and DS tooling.