Data Scientist: Industrial IoT & Water Analytics

Xylem; Sundbybergs kommun; On-site; SEK 700,000 - 900,000; Full time

Job summary

Xylem is seeking a Data Scientist to turn complex operational and sensor data into actionable insights and AI-powered solutions. You will design and deploy machine learning models, collaborate across product teams, and drive measurable value for customers and operations.

The role emphasizes strong Python skills, statistical rigor, and the ability to translate real-world problems into scalable analytics products within a global water technology context.

Qualifications

• Bachelor’s or Master’s degree in Data Science, CS, Engineering, Statistics, or a related field.
• Experience developing ML models and advanced analytics solutions.
• Strong Python skills and experience working with large or complex datasets.
• Good understanding of statistics, data analysis, and predictive modeling techniques.
• Ability to translate business and operational challenges into practical data-driven solutions.

Responsibilities

• Analyze complex operational and sensor data to uncover patterns and opportunities for improvement.
• Design, develop, validate, and deploy machine learning models and advanced analytics solutions.
• Build algorithms for forecasting, anomaly detection, and predictive decision support.
• Transform business and customer challenges into scalable, data-driven solutions.
• Collaborate with product managers, engineers, domain experts, and customers to deliver new capabilities.
• Monitor and continuously improve the performance of analytics solutions and models.

Skills

Python

Machine learning

Data analysis

Communication

Education

Bachelor’s or Master’s in Data Science or related field

Tools

Pandas

scikit-learn

TensorFlow/PyTorch

Job description

Xylem is seeking a Data Scientist to turn complex operational and sensor data into actionable insights and AI-powered solutions. You will design and deploy machine learning models, collaborate across product teams, and drive measurable value for customers and operations.

The role emphasizes strong Python skills, statistical rigor, and the ability to translate real-world problems into scalable analytics products within a global water technology context.