Data Scientist – Solar Manufacturing Analytics

Qcells North America; Cartersville (GA); On-site; USD 90,000 - 130,000; Full time

Job summary

Q CELLS North America is seeking a Data Scientist to deliver data-driven solutions for solar product manufacturing. You will reduce downtime, improve yield, and optimize processes by building forecasting models and fault-detection systems in collaboration with engineers and operators.

The role requires a Master’s or equivalent experience in a quantitative field, strong Python/SQL skills, and familiarity with ML libraries.

Qualifications

• Master's degree in a quantitative field with 2+ years of experience OR a Bachelor's with 5+ years of experience
• Strong programming and data analysis skills in Python and SQL with relational databases
• Solid knowledge of statistics and machine learning algorithms
• Experience with libraries like NumPy, SciPy, Scikit-learn; exposure to PyTorch/TensorFlow/Keras is a plus
• Ability to develop and maintain data-driven models for forecasting and process simulation
• Excellent analytical thinking and cross-functional collaboration abilities

Responsibilities

• Define engineering problems in the solar PV manufacturing process and contribute to analytical solutions with cross-functional teams
• Interface with engineers and technicians to translate requirements into actionable analytical support
• Investigate root causes of process or equipment failures and yield declines
• Develop data-driven models using historical data to forecast outcomes and predict equipment health
• Operate, monitor, and maintain existing models, fault detection systems, and process controls

Skills

Python

SQL

Statistics

Machine learning

NumPy

SciPy

Scikit-learn

PyTorch

TensorFlow

Keras

Data modeling

Cross-functional teamwork

Data visualization

Education

Master's degree in a quantitative discipline

Bachelor's degree with 5+ years relevant experience

Tools

Oracle

MS SQL

Job description

Q CELLS North America is seeking a Data Scientist to deliver data-driven solutions for solar product manufacturing. You will reduce downtime, improve yield, and optimize processes by building forecasting models and fault-detection systems in collaboration with engineers and operators.

The role requires a Master’s or equivalent experience in a quantitative field, strong Python/SQL skills, and familiarity with ML libraries.