Staff Engineer - Data Scientist

About the role

We are a Digital Product Engineering company that is scaling in a big way! We build products, services, and experiences that inspire, excite, and delight. We work on a scale across all devices and digital mediums, and our people exist everywhere in the world (18000 plus experts across 40 countries, to be exact). Our work culture is dynamic and non-hierarchical. We are looking for great new colleagues. That is where you come in!

Location: Grand-Prairie, Texas 75050
Work Model: Onsite (4 days a week work from office Mon - Thu)
Duration: Fulltime Employee

Responsibilities

• Bridge OT/IT systems for real-time data extraction using industrial protocols (OPC-UA, MQTT, Modbus)
• Build scalable cloud data pipelines for high-volume manufacturing and IoT data using Spark, Kafka, Airflow, and Delta Lake
• Move models from prototype to production in industrial environments using scikit-learn, TensorFlow, or PyTorch
• Translate complex model outputs into clear, actionable recommendations for operations and executive stakeholders
• Apply statistical methods — time series, regression, clustering, and hypothesis testing — to manufacturing quality problems
• Design A/B experiments and simulations to validate process changes and quantify business impact before full deployment
• Drive measurable gains in yield, uptime, and efficiency through applied experience with OEE, Six Sigma, SPC, and lean methodologies

Requirements

• Minimum 6 years of experience as 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 for predictive maintenance, anomaly detection, demand forecasting, and root cause analysis
• Manufacturing experience (8–10 years preferred) with hands-on experience in shop floor operations, production planning, and systems including MES, SCADA, and ERP
• Proficient in industrial protocols (OPC-UA, MQTT, Modbus) with ability to bridge OT/IT systems for real-time data extraction
• Applied experience with OEE, Six Sigma, SPC, and lean methodologies
• Skilled in building scalable cloud data pipelines for high-volume manufacturing and IoT data using Spark, Kafka, Airflow, and Delta Lake
• Proficient in scikit-learn, TensorFlow, or PyTorch with experience moving models from prototype to production in industrial environments
• Strong communicator — able to translate complex model outputs into clear, actionable recommendations for operations and executive stakeholders
• Solid grounding in statistical methods — time series, regression, clustering, and hypothesis testing applied to manufacturing quality problems
• Experience designing A/B experiments and simulations to validate process changes and quantify business impact before full deployment