Drive Industry 4.0 Transformation & Predictive Intelligence in Smart Factories

Are you a data scientist who thrives on connecting abstract algorithms with heavy machinery, IoT sensors, and real-world assembly lines? TalentXM is seeking an experienced AI/ML Manufacturing Data Scientist with 6–7 years of specialised expertise to pioneer advanced predictive analytics and process optimisation models for global industrial operations.

In this high-impact role, you will bridge the gap between complex industrial data streams and floor-level operational strategy. You won’t just build models in isolation; you will ingest high-velocity data from SCADA, MES, and IoT ecosystems to engineer predictive maintenance schedules, minimize defect leakage, and build digital twins that reshape modern manufacturing efficiency.

The Role: AI/ML Manufacturing Data Scientist

As a principal architect of manufacturing intelligence, you will build the end-to-end analytics stack—from raw sensor data pipelines to real-time alerting dashboards utilized by plant operators and senior executives.

Key Responsibilities:

• Predictive Maintenance & Telemetry: Build and deploy time-series forecasting and anomaly detection models to predict equipment failures, eliminate unplanned downtime, and optimize tool maintenance intervals.

• Process Parameter Optimization: Design and implement operations research and optimization algorithms (e.g.,linear programming, genetic algorithms) to dynamically tune process parameters, improve asset throughput, and reduce waste.

• Operational Decision Support: Translate sophisticated AI model outputs into intuitive, real-time decision-support tools, streaming dashboards, and automated alert systems for factory floor operators.

• Data Pipeline & MES/SCADA Integration: Partner with data engineers to construct and maintain scalable pipelines that ingest, clean, and unify structured data from Manufacturing Execution Systems (MES), SCADA setups, and edge IoT devices.

• Cross-Functional Collaboration: Partner with process engineers, production supervisors, and maintenance personnel to validate that AI models align with physical constraints, safety regulations, and operational realities.

Technical Architecture & Prerequisites

We are looking for a hybrid professional who pairs elite algorithmic data science capabilities with a pragmatic understanding of industrial shop floors.

Required Qualifications:

• Experience: 6–7 years of dedicated experience in data science or predictive analytics, heavily centered within manufacturing, heavy industry, or high-volume production environments.

• Machine Learning Stack: Expert-level mastery of Python and standard ML frameworks, including scikit-learn, TensorFlow, and PyTorch.

• Data Manipulation: Advanced SQL optimisation skills alongside deep practical experience in signal processing, statistical data cleaning, and sensor feature engineering.

• Manufacturing Acumen: Concrete familiarity with industrial control concepts, quality management systems, equipment reliability frameworks, and operational data models.

Preferred Skills (Industry 4.0 Focus):

• Advanced AI: Practical application of Deep Learning, Reinforcement Learning, or Computer Vision for industrial defects inspection.

• Cloud & Big Data: Experience scaling AI solutions inside cloud infrastructure (AWS, Azure, or GCP) using distributed compute processing engines like Apache Spark or Hadoop.

• Smart Factory Vision: Familiarity with Industry 4.0 blueprints, edge computing, and Digital Twin design.

• BI Visualisation: Proficiency in creating factory-floor operational dashboards inside Tableau or Power BI.

What We Offer

• High architectural ownership: Lead the shift from reactive operations to a highly predictive, automated manufacturing structure.

• Complex physical datasets: Solve data challenges involving multi-million dollar machinery networks and ultra-high frequency IoT telemetry.