WE ARE LOOKING FOR

Senior Data Scientist
We’re seeking a technically skilled and business-oriented Senior Data Scientist to lead industrial data science projects in the IoT and manufacturing sectors. In this role, you’ll develop models that optimize operations, predict machine behavior and drive smart automation in complex environments like heavy industry, chemicals, logistics, and energy.
As a core team member, you will work with industrial clients to unlock value from sensor data, ERP systems, and other data sources—applying advanced machine learning methods and anomaly detection techniques to real-world challenges.

As part of this role, you will work on tasks such as:

• Predicting machine failure and maintenance needs (RUL modeling)
• Creating statistical models for optimizing production efficiency
• Building forecasting tools for energy usage and transportation flows
• Analyzing operational data to support investment and upgrade decisions

Key Responsibilities:

• Develop predictive and anomaly detection models for sensor-rich environments (e.g., predictive maintenance, lifecycle analysis)
• Collaborate with clients and engineers to scope business problems and design data-driven solutions
• Analyze time-series and unstructured data using machine learning, deep learning, and statistical techniques
• Create interpretable models to support diagnostics and operational decisions
• Build and deliver insights through dashboards, applications, and model visualizations
• Contribute to long-term analytics strategies and research in the industrial domain

Skills Required

REQUIRED QUALIFICATIONS

• 5+ years of experience in data science, preferably with industrial or IoT use cases
• Strong skills in Python, R, SQL and time-series analytics
• Experience with anomaly detection, clustering and deep learning for sensor data
• Familiarity with cloud platforms such as AWS or Azure
• Background in statistics, engineering or applied machine learning
• Bonus: Experience with manufacturing or industrial clients

As part of this role, you will work on tasks such as:

• Predicting machine failure and maintenance needs (RUL modeling)
• Creating statistical models for optimizing production efficiency
• Building forecasting tools for energy usage and transportation flows
• Analyzing operational data to support investment and upgrade decision

Key Responsibilities:

• Develop predictive and anomaly detection models for sensor-rich environments (e.g., predictive maintenance, lifecycle analysis)
• Collaborate with clients and engineers to scope business problems and design data-driven solutions
• Analyze time-series and unstructured data using machine learning, deep learning, and statistical techniques
• Create interpretable models to support diagnostics and operational decisions
• Build and deliver insights through dashboards, applications, and model visualizations
• Contribute to long-term analytics strategies and research in the industrial domai