Job Responsibilities:
POSITION SUMMARY:
The Senior Data Scientist – Predictive Analytics for Manufacturing will play a critical role in developing machine learning models that drive reliability, efficiency, and quality improvements across global production environments. This role focuses on predictive modeling for downtime, quality issues, and process optimization using condition-based monitoring and real-time equipment data.
The ideal candidate has deep experience in applying AI/ML in manufacturing contexts, especially around time-series forecasting, anomaly detection, and predictive maintenance. They will work closely with engineering, data, and operations teams to translate sensor data and equipment telemetry into scalable, high-impact solutions.
ESSENTIAL DUTIES & RESPONSIBILITIES:
Develop machine learning models to predict downtime, detect process anomalies, and reduce quality risk based on operational and sensor data.
Analyze and model time-series data from PLCs, historians, SCADA, and IoT platforms.
Collaborate with Data Engineers and IoT Developers to ensure availability, structure, and integrity of real-time data.
Work directly with plant operations and engineering teams to identify predictive use cases and validate model outcomes.
Deploy and monitor models in production environments (cloud or edge) with appropriate feedback and retraining cycles.
Document model development, performance, assumptions, and dependencies for traceability and knowledge transfer.
Partner with leadership to assess business value and model ROI in predictive maintenance and operational improvement use cases.
Stay current with best practices and advancements in AI/ML, particularly within manufacturing applications.
The above is intended to describe the general content of and the requirements for the performance of this position. It is not to be construed as an exhaustive statement of duties, responsibilities, or requirements.
QUALIFICATIONS:
To perform this job successfully, an individual must be able to perform each essential duty and responsibility satisfactorily. The requirements listed below are representative of the knowledge, skill, ability and/or physical demands required. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.
Proficient in Python and ML libraries such as scikit-learn, XGBoost, TensorFlow, or similar.
Hands-on experience with time-series modeling, anomaly detection, and condition-based monitoring applications.
Familiarity with manufacturing KPIs, equipment telemetry, and industrial datasets (vibration, temperature, cycle time, etc.).
Experience with cloud-based ML pipelines and MLOps practices (Azure, AWS, or other).
Excellent communication and problem-solving skills in a cross-functional manufacturing environment.
Education/Special Knowledge - bachelor’s or master’s degree in data science, Computer Engineering, Mechanical Engineering, or a related field. Industrial/Manufacturing domain experience preferred.
Experience - 6+ years of experience building and deploying machine learning models in production environments.
Physical Demands/Work Environment - Normal amount of sitting or standing, average mobility to move around an office environment, able to conduct normal amount of work at a computer, may require local, domestic and international travel. This position will be located out of Troy MI, or remote with a travel requirement.
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