Job Description:
Experience in data science, machine learning or applied analytics, including leadership of production AI solutions.
Robust Python, SQL, statistics, experimentation and machine-learning fundamentals.
Hands-on experience with supervised/unsupervised methods, time-series modelling, anomaly detection, optimization and model evaluation.
Experience productionizing models through MLOps, APIs, containers, automated testing, monitoring and cloud platforms.
Ability to work with noisy, sparse and multi-rate industrial data and link model performance to manufacturing outcomes.
Understanding of responsible AI, explainability, security, model risk and operational controls.
Robust stakeholder management, technical leadership and communication skills.
Bachelor's or master's degree in engineering, statistics, mathematics, computer science or a related discipline.