Job Description

The IT Data Senior Scientist will leverage advanced analytics, machine learning, and statistical methods to extract meaningful insights from complex datasets. In this role, they will develop and implement data models, conduct in-depth analysis, and collaborate with cross-functional teams to drive data-driven decision-making. They will work with large datasets to identify patterns, build predictive models, and provide actionable recommendations that support business strategies. This position offers the opportunity to work with cutting-edge technologies and mission-critical AI-based business cases, and solve key challenges through data innovation.

Must have skills:

-Machine Learning Model Development and Deployment

-Industrial Data Science and IoT/Time Series (Critical for working with sensor data from manufacturing sources (IoT/Industry 4.0)

-Computer Vision (CV): Specific experience with AI-driven solutions like computer vision for automate product inspection and identifying defects, which requires technical familiarity with CV libraries like OpenCV and deep learning frameworks like TensorFlow/PyTorch.

-Working with large datasets and deploying cutting-edge AI requires a scalable, cloud-based infrastructure.

Key Responsibilities

• Gather, preprocess, and clean data from various manufacturing sources (e.g., sensors, production systems) to ensure high-quality, accurate datasets for analysis.
• Develop machine learning models to predict equipment failures, enabling proactive maintenance and minimizing downtime on the manufacturing floor.
• Implement AI-driven solutions such as computer vision and statistical models to automate product inspection, identify defects, and maintain product quality.
• Analyze production processes to identify inefficiencies, bottlenecks, and opportunities for optimization, recommending data-driven strategies to improve throughput and reduce costs.
• Use data analytics to optimize supply chain operations by forecasting demand, improving inventory management, and enhancing logistics to reduce lead times and costs.
• Build and refine predictive models to forecast production schedules, optimize resource allocation, and improve capacity planning based on historical data and trends.
• Design and deploy anomaly detection algorithms to monitor production systems, identifying unusual patterns or failures in real-time to prevent costly errors.
• Work closely with production, engineering, and IT teams to understand business needs, develop solutions, and integrate data science tools into manufacturing workflows.
• Create dashboards, visualizations, and reports to effectively communicate insights and trends to stakeholders and support data-driven decision-making.
• Stay updated on emerging data science techniques and technologies, driving continuous improvements in manufacturing processes and introducing innovative solutions to enhance productivity.

Required Education, Experience, and Skills

Minimum Education Level: Bachelor's

Specialized Degree: Software Engineering, Applied Computer Science, Statistics.

Years of Experience: 5-7 years

Field of Expertise: Manufacturing, ioT, Industry 4.0, Cybersecurity,

Preferred Education, Experience, and Skills

Minimum Education Level: Master's

Certificates: GCP, AW, S, or Azure certified

Years of Experience: 8-11 years

Preferred Field of Expertise: Manufacturing in Wire & Cable

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