Predictive Analytics Specialist

Achieve Tangible Business Impact

You work hands-on with industrial time-series data, combining solid analytical foundations with modern AI techniques to identify patterns, anomalies, and insights in complex systems. In close collaboration with senior experts, business stakeholders, and external partners (including academia), you support the development and deployment of analytics solutions that bridge rigorous analytical thinking with tangible business impact.

What You’ll Do

• Apply data analytics, statistical methods, and AI techniques to analyze complex industrial time-series data.
• Support the development, testing, and validation of Predictive Analytics and AI models under guidance of senior team members.
• Contribute to use cases such as anomaly detection, condition monitoring, forecasting, and root-cause analysis in operational data.
• Work with domain experts and business stakeholders to translate technical and business questions into structured analytical tasks.
• Balance academic rigor (sound methods, validation, documentation) with a strong focus on practical impact and scalability.
• Aid in documenting methodologies, results, and best practices to enable reuse across projects and teams.
• Collaborate with internal teams and external partners from industry and academia on analytics and AI initiatives.

Qualifications

• Master’s degree in data science, computer science, physics, mathematics, engineering, or a related quantitative field; PhD is a plus.
• Strong foundation in data analytics, statistics, and machine learning.
• Relevant business experience or strong academic background in time-series analysis, including feature engineering using autoregressive techniques and advanced machine-learning and deep-learning approaches for real-world data.
• 2+ years of hands-on experience with programming languages and tools for data analysis and AI (e.g., Python, R, JavaScript and TypeScript, SQL, TensorFlow, PyTorch).
• Ability to structure analytical problems, work with large and complex datasets, and communicate results clearly.
• Intellectual curiosity, motivation to learn, and ability to work effectively in a multidisciplinary, global team environment.