My client is a pioneering provider of intelligent corrosion monitoring and analytics solutions for critical industrial asset integrity challenges. Our innovative sensing technologies and predictive analytics empower businesses to remotely monitor and forecast risks, enabling data-driven decision-making in asset management.

As a Data Scientist, you will play a crucial role in developing complex data analysis, interpretation, and visualization solutions. Collaborating closely with our software team, you will contribute to building production algorithms as part of our IoT platform. Additionally, you will support laboratory activities, including experiments, to expand our database and refine algorithms for greater accuracy.

Key Responsibilities:

• Develop new features and models for the analytics platform of our products.
• Utilize analytical, statistical, and machine learning techniques to interpret sensor data for detecting and predicting industrial asset integrity.
• Translate Risk Base Inspection standards into real-time algorithms integrated with monitoring systems.
• Generate client reports with data insights and advisory services.
• Build strong relationships and collaborate with clients and colleagues.
• Undertake pre-processing of structured and unstructured data.
• Analyze large datasets to discover trends and patterns.
• Develop predictive models and machine-learning algorithms.
• Ensure unit testing and deliver working software according to company standards.
• Document algorithms and data processing methods.

Key Skills and Experience:

• Proficiency in Agile/Scrum methodology and framework.
• Experience with project management tools.
• Strong programming skills in Python (NumPy, Pandas, Matplotlib, Scikit-Learn, scikit-rf, SciPy).
• Familiarity with relational databases.
• Advanced Excel skills and UI prototyping.
• Lab experiments design and development experience.
• Knowledge of data analytics and signal processing techniques.
• MSc or PhD in science, mathematics, or engineering.