Description

SUMMARY

The Senior Data Analyst will deliver data-driven solutions to address challenges in solar product manufacturing. By leveraging advanced analytics, you will help reduce downtime, increase yield and productivity, identify and resolve potential issues proactively, and optimize manufacturing processes enabling the delivery of higher-quality products to customers.

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.

Required Qualifications

Bachelor’s degree in a quantitative discipline (e.g., Computer Science, Statistics, Industrial Engineering, Electrical Engineering, Chemical Engineering) with 10+ years of relevant experience.
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.
Excellent analytical thinking and communication skills, with the ability to collaborate effectively across cross-functional teams.

Preferred Qualifications

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.
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.
Proficiency in data visualization tools such as Spotfire, Tableau, or Power BI.
Familiarity with big data technologies like Hadoop, Spark, and Kafka.
Experience developing digital twins for manufacturing systems.

Hanwha Q CELLS provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion, sex, national origin, age, disability, or genetics.

Qcells North America

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