Staff Engineer - Data Scientist

We are a Digital Product Engineering company scaling globally, building products, services, and experiences that inspire and delight. With over 18,000 experts across 40 countries, we foster a dynamic, non-hierarchical work culture.

About the role

This onsite role (4 days a week in the office Monday–Thursday) is based in Grand Prairie, Texas. You’ll bridge operational technology (OT) and IT systems to extract real-time data, applying data science and engineering to drive measurable gains in manufacturing efficiency, yield, and uptime.

Responsibilities

• Design and build scalable cloud data pipelines for high-volume manufacturing and IoT data using Spark, Kafka, Airflow, and Delta Lake.
• Develop and deploy machine learning models for predictive maintenance, anomaly detection, demand forecasting, and root cause analysis in industrial environments.
• Apply statistical methods (time series, regression, clustering, hypothesis testing) to manufacturing quality problems.
• Translate complex model outputs into clear, actionable recommendations for operations and executive stakeholders.
• Design A/B experiments and simulations to validate process changes and quantify business impact before full deployment.
• Bridge OT/IT systems using industrial protocols (OPC-UA, MQTT, Modbus) for real-time data extraction.
• Leverage OEE, Six Sigma, SPC, and lean methodologies to improve yield, uptime, and efficiency.

Requirements

• Minimum 6 years of experience as a Data Scientist.
• Strong SQL and Python proficiency with hands-on experience in medallion/lakehouse architectures on Databricks, Snowflake, AWS, or Azure.
• Proven track record building and deploying ML models (scikit-learn, TensorFlow, or PyTorch) in production for industrial use cases.
• Experience with shop floor operations, production planning, and systems including MES, SCADA, and ERP (8–10 years in manufacturing preferred).