onsite
Senior Data Scientist - Industrial Applications
Data Scientist
Lead advanced analytics and AI solutions for industrial processes, leveraging Python, deep learning, computer vision, and cloud platforms (AWS, Azure) to drive data‑driven decision making and operational efficiency.
About the role
Key Responsibilities
- Design, develop, and deploy end‑to‑end machine‑learning pipelines for predictive maintenance, quality control, and process optimization in an industrial environment.
- Apply deep learning and computer‑vision techniques to analyze sensor, image, and video data from manufacturing lines.
- Collaborate with domain experts and engineering teams to translate business problems into data‑science solutions and integrate models into production systems.
- Utilize AWS and Azure services (e.g., SageMaker, Azure ML, Data Lake, IoT Hub) for scalable model training, serving, and monitoring.
- Implement data‑engineering best practices, including data ingestion, cleaning, feature engineering, and versioning to ensure high‑quality datasets.
Requirements
- 5+ years of professional experience in data science or machine learning, preferably in an industrial or manufacturing context.
- Strong proficiency in Python and its data‑science ecosystem (pandas, NumPy, scikit‑learn, PyTorch/TensorFlow).
- Hands‑on experience with deep learning architectures for computer vision (CNNs, object detection, segmentation).
- Proven track record deploying models on cloud platforms such as AWS and Azure, including CI/CD pipelines and monitoring.
- Solid understanding of data engineering concepts, relational and time‑series databases, and big‑data processing frameworks.
Skills
pythonmachine learningdeep learningcomputer visionawsazure