Data Scientist
Q-Cells
Description
SUMMARY The Data Scientist will deliver data-driven solutions to address challenges in solar product manufacturing. By leveraging analytics, you will help reduce downtime, increase yield and productivity, identify and resolve potential issues proactively, and support the optimization of manufacturing processes to enable the delivery of higher-quality products to customers. Responsibilities
SUMMARY The Data Scientist will deliver data-driven solutions to address challenges in solar product manufacturing. By leveraging analytics, you will help reduce downtime, increase yield and productivity, identify and resolve potential issues proactively, and support the optimization of manufacturing processes to enable the delivery of higher-quality products to customers. Responsibilities
- Help define engineering problems in the solar PV manufacturing process and contribute to analytical solution development in collaboration with cross-functional teams
- Interface with engineers and technicians to gather and translate requirements into actionable analytical support for process operations
- Support investigations into the root causes of process or equipment failures, unexpected shutdowns, and declines in yield, productivity, or efficiency
- Develop data-driven models using historical data to forecast outcomes, predict equipment health, and simulate operating conditions
- Operate, monitor, and maintain existing data-driven models, fault detection systems, and process control systems
- Master's degree in a quantitative discipline (e.g., Computer Science, Statistics, Industrial Engineering, Electrical Engineering, Chemical Engineering) with 2+ years of relevant experience (or a Bachelor's degree with 5+ years of relevant experience)
- Programming and data analysis skills using Python and SQL, with experience in relational databases (e.g., Oracle, MSSQL) and querying complex datasets
- Working knowledge of statistics and machine learning algorithms
- Experience using statistical and machine learning libraries (e.g., NumPy, SciPy, Scikit-learn); exposure to deep learning frameworks (e.g., PyTorch, TensorFlow, Keras) is a plus
- Ability to develop and maintain data-driven models for forecasting, equipment health prediction, and process simulation
- Strong analytical thinking and communication skills, with the ability to collaborate effectively across cross-functional teams
- Experience in a data-focused role within the solar PV, display device, or semiconductor manufacturing industry
- Experience with Fault Detection and Classification (FDC) and Advanced Process Control (APC) systems in a manufacturing environment
- Familiarity with cloud platforms (AWS, Azure, or GCP) for data pipelines, storage, or model deployment
- Exposure to retrieval-augmented generation (RAG) or LLM-based applications for industrial data and knowledge management
Vacancy posted 4 days ago
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