Data Scientist

Qcells North America; Cartersville (GA); On-site; USD 110,000 - 140,000; Full time

Job summary

Qcells North America is seeking a Data Scientist to deliver data-driven solutions for solar product manufacturing. You will help reduce downtime, improve yield, and optimize processes by building forecasting models and monitoring systems across cross-functional teams.

The role requires a Master’s in a quantitative field or a Bachelor’s with extensive experience, with strong Python/SQL skills and knowledge of ML libraries. Collaboration with engineers and technicians is essential to success.

Qualifications

• Master’s degree in a quantitative field with 2+ years of relevant experience, or a Bachelor’s with 5+ years of relevant experience.
• Programming and data analysis 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

Responsibilities

• Define engineering problems in the solar PV manufacturing process and contribute to analytical solution development with cross-functional teams
• Interface with engineers and technicians to translate requirements into actionable analytical support for process operations
• Investigate root causes of process or equipment failures, and declines in yield, productivity, or efficiency
• Develop data-driven models to forecast outcomes, predict equipment health, and simulate operating conditions
• Operate, monitor, and maintain data-driven models, fault detection systems, and process control systems

Skills

Data analysis

Statistics

Machine learning

Cross-functional collaboration

Communication

Forecasting

Process simulation

Education

Master’s degree in a quantitative field

Bachelor’s degree + 5+ years experience

Tools

Python

SQL

Oracle MSSQL

NumPy

SciPy

Scikit-learn

PyTorch

TensorFlow

Keras

Deep Learning

Job description

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

• 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

Required Qualifications

• 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

Preferred Qualifications

• 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