Manufacturing 8–10 years in manufacturing (optional) 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 to drive measurable gains in yield, uptime, and efficiency.
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.
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.