The Senior Data Analyst will deliver data-driven solutions to address challenges in solar product manufacturing, aiming to reduce downtime, increase yield and productivity, identify and resolve potential issues proactively, and optimize manufacturing processes.
Requirements
- Strong programming and data analysis skills using Python and SQL, with experience in relational databases (e.g., Oracle, MSSQL) and querying complex datasets.
- Solid foundation in statistics, machine learning algorithms, and control theory (including PID Control, Model Predictive Control, and Run-to-Run control).
- Proficient in using statistical and machine learning libraries (e.g., NumPy, SciPy, Scikit-learn) and deep learning frameworks (e.g., PyTorch, TensorFlow, Keras).
- Demonstrated ability to develop and maintain data-driven models for forecasting, equipment health prediction, and process simulation.
- Experience in a data-focused role within the solar PV, display device, or semiconductor manufacturing industry.
- Knowledge of automation engineering, including PLC programming, human-machine interfaces (HMIs), and machine-to-machine communication.
- Familiarity with big data technologies like Hadoop, Spark, and Kafka.
Responsibilities
- Define engineering problems in the solar PV manufacturing process and lead 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.
- Investigate and determine 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 various operating conditions.
- Operate, monitor, and maintain existing data-driven models, fault detection systems and process control systems.
Other
- Excellent analytical thinking and communication skills, with the ability to collaborate effectively across cross-functional teams.
- Bachelor’s degree in a quantitative discipline (e.g., Computer Science, Statistics, Industrial Engineering, Electrical Engineering, Chemical Engineering) with 10+ years of relevant experience.
- Master’s degree in a quantitative discipline (e.g., Computer Science, Statistics, Industrial Engineering, Electrical Engineering, Chemical Engineering or a related field) with 5+ years of relevant experience.
- Proficiency in data visualization tools such as Spotfire, Tableau, or Power BI.
- Experience developing digital twins for manufacturing systems.
